CRITIC

CRITIC (CRiteria Importance Through Intercriteria Correlation) is a weight objective multi-criteria decision-making (MCDM) method introduced by Diakoulaki, D., Mavrotas, G., Papayannakis, L. in 1995. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Statistical contrast intensity + correlation-based objective weighting

Diakoulaki, D., Mavrotas, G., Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research

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Critical Autoethnography

CAE
critical auto-ethnography
critical self-ethnography
critical performative autoethnography

2000s–2010s (crystallised as named approach ~2012)

Robin M. Boylorn, Mark P. Orbe (editors of foundational volume); D. Soyini Madison (critical ethnography lineage)

Critical autoethnography combines the self-reflective personal narrative of autoethnography with the social-justice orientation of critical theory. The researcher uses their own lived experience as primary data to interrogate power structures, systemic inequalities, and cultural norms — treating the personal not merely as testimony but as a site for political and theoretical critique. It is widely used to center the voices of marginalized groups and challenge dominant social narratives.

Personal narrative, field notes, autoethnographic texts, performative vignettes

Madison, D. S. (2005). Critical Ethnography: Method, Ethics, and Performance. Sage.

Boylorn, R. M., & Orbe, M. P. (Eds.). (2012). Critical Autoethnography: Intersecting Cultural Identities in Everyday Life. Left Coast Press.

autoethnography critical-ethnography interpretive-autoethnography narrative-inquiry critical-discourse-analysis reflexive-thematic-analysis


Critical Case Law Analysis

critical legal analysis
CLS case analysis
critical judicial analysis
critical legal reading

Late 1970s–1980s (CLS conference 1977; Unger 1983)

Critical Legal Studies (CLS) movement; key figures include Duncan Kennedy, Roberto Unger, Mark Tushnet

Critical case law analysis applies the theoretical tools of Critical Legal Studies (CLS) to the examination of judicial decisions. Rather than accepting legal reasoning at face value, this approach interrogates how courts construct legal arguments, whose interests those arguments serve, and how ideological commitments are concealed beneath the appearance of neutral doctrinal logic. It exposes the political and social dimensions embedded in judicial language and outcomes.

Court opinions, judicial decisions, legal texts

Unger, R. M. (1983). The Critical Legal Studies Movement. Harvard Law Review, 96(3), 561–675.

Kennedy, D. (1976). Form and Substance in Private Law Adjudication. Harvard Law Review, 89(8), 1685–1778.

case-law-analysis doctrinal-legal-research comparative-legal-analysis legal-content-analysis hermeneutic-analysis discourse-analysis


Critical case study

critical case
strategic case study
critical-instance case study
paradigmatic case study

Bent Flyvbjerg (formalized); Robert K. Yin (case study typology)

A critical case study is a case study design in which the researcher deliberately selects a case that is strategically important for testing, confirming, challenging, or extending an existing proposition, theory, or policy claim. Rather than choosing a typical or representative case, the researcher argues that if the finding holds here — in this most-likely, least-likely, or paradigmatic instance — it can reasonably be expected to hold more broadly. This purposive logic transforms a single case into a powerful analytical tool.

Interviews, documents, observations, archival records

Flyvbjerg, B. (2006). Five misunderstandings about case-study research. Qualitative Inquiry, 12(2), 219–245.

Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage.

case-study interpretive-case-study comparative-case-study grounded-theory critical-ethnography critical-discourse-analysis


Critical constructivist grounded theory

Emancipatory constructivist grounded theory

Kathy Charmaz (constructivist GT base); synthesis with critical theory by various scholars (e.g., Belfrage, Hauf; Street; Wuest)

Critical constructivist grounded theory combines Kathy Charmaz's constructivist grounded theory with an explicit critical theoretical lens — typically feminist, critical race, or Freireian frameworks — to generate theory that not only explains a social process but also interrogates power relations, structural inequalities, and ideological forces that shape participants' experiences. The result is grounded theory with an emancipatory intent.

Interviews, documents, field notes, participant observations

Charmaz, K. (2014). Constructing Grounded Theory (2nd ed.). Sage.

Belfrage, C., & Hauf, F. (2017). The Gentle Art of Retroduction: Critical Realism, Cultural Political Economy and Critical Grounded Theory. Organization Studies, 38(2), 251–271.


Critical Content Analysis

CCA
critical textual analysis
ideological content analysis
critical qualitative content analysis

1980s–2000s (consolidated in practice by the 1990s–2000s)

Building on Krippendorff (1980) and Altheide (1996); synthesised through critical theory traditions (Frankfurt School, feminist and race critical scholars)

Critical content analysis is a qualitative approach that examines texts, media, and documents not merely for manifest meaning but for how they construct, reinforce, or contest relations of power, ideology, race, gender, and class. Grounded in critical theory traditions, it asks whose interests a text serves, what voices are silenced, and how language and representation naturalise dominant worldviews. It combines systematic analytic rigour with an explicitly emancipatory or transformative research stance.

Textual, visual, or multimodal documents and media

Altheide, D. L. (1996). Qualitative Media Analysis. Sage.

Rogers, R., Malancharuvil-Berkes, E., Mosley, M., Hui, D., & Joseph, G. O. (2005). Critical Discourse Analysis in Education: A Review of the Literature. Review of Educational Research, 75(3), 365–416.

critical-discourse-analysis interpretive-content-analysis thematic-analysis critical-thematic-analysis semiotic-analysis critical-qualitative-content-analysis


Critical Curriculum Analysis

CCA
critical curriculum inquiry
critical curriculum critique
curriculum critique

Michael W. Apple; Henry A. Giroux; Paulo Freire (critical pedagogy foundations)

Critical curriculum analysis examines educational curricula — their content, organisation, and underlying assumptions — through a critical theory lens. Drawing on the work of Apple, Giroux, and Freire, it asks whose knowledge counts, whose interests the curriculum serves, and how schooling reproduces or challenges social inequalities. Rather than treating curriculum as neutral, it treats it as an ideologically saturated artifact shaped by relations of power, race, class, and gender.

Curriculum documents, textbooks, policy texts, standards, syllabi

Apple, M. W. (1979). Ideology and Curriculum. Routledge & Kegan Paul.

Giroux, H. A. (1997). Pedagogy and the Politics of Hope: Theory, Culture, and Schooling. Westview Press.

curriculum-analysis critical-discourse-analysis educational-action-research hermeneutic-analysis critical-textual-criticism program-evaluation


Critical Digital Ethnography

CDE
critical online ethnography
critical virtual ethnography
digital critical ethnography

Synthesised from critical ethnography (Thomas, 1993) and digital/virtual ethnography (Hine, 2000); scholars including Bhatt, de Roock, and Saldanha developed explicit critical-digital frameworks from the 2010s onward

Critical digital ethnography is a qualitative research design that combines the immersive, participatory observation of digital ethnography with the power-conscious, emancipatory orientation of critical theory. Researchers embed themselves in online communities, platforms, or digital practices and examine not only what people do online but also how digital spaces reproduce, challenge, or transform structures of power, inequality, and identity. It is widely used in education, communication studies, and social science.

Online field notes, digital artefacts, screenshots, social media data, interviews, chat logs

Bhatt, I., & de Roock, R. (2013). Capturing the sociomateriality of digital literacy events. Research in Learning Technology, 21. https://doi.org/10.3402/rlt.v21.21624

Pennycook, A. (2012). Language and Mobility: Unexpected Places. Multilingual Matters.

digital-ethnography netnography critical-ethnography critical-discourse-analysis virtual-ethnography participatory-action-research


Critical Discourse Analysis

CDA
Critical Linguistics
Discourse-Historical Approach
Dialectical-Relational Analysis

Late 1970s–1990s (systematised ~1979–1995)

Norman Fairclough; Teun A. van Dijk; Ruth Wodak

Critical Discourse Analysis (CDA) is a qualitative method that examines how language in texts and talk constructs, sustains, and challenges relations of power, ideology, and social inequality. Drawing on linguistics, social theory, and critical philosophy, CDA treats discourse not merely as communication but as social practice — a site where dominance is reproduced and where resistance can be articulated. Developed in the late twentieth century by Norman Fairclough, Teun van Dijk, and Ruth Wodak, among others, CDA is applied to political speeches, media texts, policy documents, educational materials, and institutional interactions.

Written texts, media discourse, political speeches, institutional documents, interview transcripts

Purposively selected texts or episodes; sample size varies from a single document to dozens of texts

Fairclough, N. (1992). Discourse and Social Change. Polity Press.

van Dijk, T. A. (1993). Principles of critical discourse analysis. Discourse and Society, 4(2), 249–283.

discourse-analysis narrative-analysis thematic-analysis content-analysis ethnography grounded-theory


Critical Doctrinal Legal Research

critical legal doctrinal analysis
critical black-letter research
critical legal doctrine
CLS-informed doctrinal research

1970s–1980s (Critical Legal Studies movement; applied to doctrinal method from 1980s onward)

Synthesized from Traditional Doctrinal Legal Research and Critical Legal Studies (Roberto Unger, Duncan Kennedy, and others)

Critical doctrinal legal research combines traditional black-letter legal analysis — systematically mapping the rules, principles, and doctrines found in statutes and case law — with the evaluative lens of critical legal theory. Rather than treating legal doctrine as a neutral or self-contained system, it interrogates the ideological assumptions, power relations, and social consequences embedded in legal rules, asking not only what the law says but whose interests it serves and what alternatives it forecloses.

Primary legal sources (statutes, case law, regulations), secondary legal literature, doctrinal texts

Hutchinson, T. (2013). Doctrinal Research: Researching the Law. In D. Watkins & M. Burton (Eds.), Research Methods in Law. Routledge.

doctrinal-legal-research comparative-legal-analysis legal-content-analysis hermeneutic-analysis case-law-analysis critical-discourse-analysis


Critical Document Analysis

CDA-doc
critical documentary analysis
critical policy document analysis
critical textual document analysis

Late 20th – early 21st century (2000s–present as an explicit variant)

Glenn Bowen; Lindsay Prior (foundational document analysis); critical theory tradition (Freire, Habermas)

Critical document analysis is a qualitative method that systematically examines written, visual, or digital documents — such as policy texts, institutional reports, curriculum materials, and official records — through a critical theoretical lens. Rather than treating documents as neutral containers of information, it interrogates how documents produce, reflect, and reproduce power relations, ideologies, and social inequalities. The approach draws on critical theory traditions, including the work of Paulo Freire and Jurgen Habermas, as well as established frameworks for document analysis developed by Bowen and Prior.

Qualitative research design and analytic method

Textual documents (policy texts, official reports, institutional records, curriculum materials, media texts)

Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40.

Prior, L. (2003). Using Documents in Social Research. Sage.

critical-discourse-analysis interpretive-document-analysis critical-content-analysis critical-thematic-analysis document-analysis critical-qualitative-content-analysis


Critical Educational Action Research

Critical-Emancipatory Educational Action Research

critical participatory action research in education

Critical educational action research is a cyclical, participatory research design in which educators collaboratively examine and transform their own practice through iterative cycles of planning, action, observation, and critical reflection. Grounded in critical theory, it goes beyond improving techniques to questioning the social, institutional, and ideological conditions that shape educational practice, aiming at emancipation from unjust or oppressive structures.

Qualitative participatory research design

Observations, interviews, reflective journals, documents, meeting records

Carr, W., & Kemmis, S. (1986). Becoming Critical: Education, Knowledge and Action Research. Falmer Press.

Kemmis, S., & Wilkinson, M. (1998). Participatory action research and the study of practice. In B. Atweh, S. Kemmis, & P. Weeks (Eds.), Action Research in Practice (pp. 21–36). Routledge.

educational-action-research participatory-action-research critical-ethnography critical-discourse-analysis collaborative-inquiry practitioner-research


Critical Ethnography

critical ethnographic research
critical qualitative ethnography
advocacy ethnography
emancipatory ethnography

Late 20th century (~1980s–1993 systematisation)

Jim Thomas (systematised); rooted in Frankfurt School critical theory (Adorno, Horkheimer) and feminist/postcolonial traditions

Critical ethnography is a qualitative research approach that combines sustained fieldwork immersion with explicit critical theory to examine how power, inequality, and ideology shape the lived experiences of marginalised communities. Unlike conventional ethnography, which aims to describe a culture as it is, critical ethnography commits the researcher to questioning what is taken for granted and to producing knowledge that can serve as a resource for social change. Rooted in Frankfurt School critical theory and expanded through feminist, postcolonial, and race-critical traditions, it treats the research process itself as a political act.

Participant observation fieldnotes, interviews, documents, artefacts, audio-visual materials

One community or setting; sustained fieldwork of weeks to months with multiple participants

Thomas, J. (1993). Doing Critical Ethnography. Sage Publications.

Madison, D. S. (2012). Critical Ethnography: Method, Ethics, and Performance (2nd ed.). Sage Publications.

ethnography action-research discourse-analysis narrative-analysis grounded-theory phenomenology


Critical Hermeneutic Analysis

critical hermeneutics
critical-interpretive analysis
emancipatory hermeneutics
CHA

1970s (Habermas); extended through 1980s–1990s

Jürgen Habermas (critical hermeneutics); Paul Ricoeur (hermeneutics of suspicion)

Critical hermeneutic analysis combines interpretive hermeneutics with critical social theory to read texts and discourse not only for meaning but for embedded power relations, ideological distortions, and structures of domination. Originating in Habermas's critique of Gadamer and developed further by Ricoeur's hermeneutics of suspicion, the method asks both 'what does this text mean?' and 'whose interests does this meaning serve?'. It is widely used in education, social work, policy research, and health humanities.

Qualitative interpretive research approach

Texts, documents, transcripts, institutional discourse

Habermas, J. (1970). On Systematically Distorted Communication. Inquiry, 13(1–4), 205–218.

Ricoeur, P. (1981). Hermeneutics and the Human Sciences: Essays on Language, Action and Interpretation. Cambridge University Press.

hermeneutic-analysis critical-discourse-analysis critical-theory phenomenology narrative-analysis textual-criticism


Critical Hermeneutic Phenomenology

Critical Hermeneutic Phenomenological Research

hermeneutic phenomenology with critical lens

1960s–1990s (Gadamer 1960; van Manen 1990; critical synthesis developed through 1990s–2000s)

Hans-Georg Gadamer (hermeneutic tradition); Max van Manen (pedagogical application); influenced by Frankfurt School critical theory

Critical hermeneutic phenomenology is a qualitative research approach that combines Gadamerian hermeneutics — the philosophical study of interpretation — with critical social theory to examine both the lived meaning of experience and the structural, ideological, and power-laden conditions that shape it. It asks not only 'what is this experience like?' but also 'what historical, social, and political forces produce and constrain it?' The approach is widely used in education, nursing, social work, and the human sciences.

In-depth interviews, field texts, documents, narratives (text data)

van Manen, M. (1990). Researching Lived Experience: Human Science for an Action Sensitive Pedagogy. State University of New York Press.

Gadamer, H.-G. (1975). Truth and Method (G. Barden & J. Cumming, Trans.). Seabury Press. (Original work published 1960).

hermeneutic-phenomenology interpretive-hermeneutic-phenomenology critical-phenomenology critical-discourse-analysis critical-ethnography interpretive-phenomenology


Critical Institutional Ethnography

institutional ethnography with critical orientation

1987 (IE foundational); critical applications prominent 1990s–2000s

Dorothy E. Smith (institutional ethnography); critical variant developed through feminist and critical scholars

Critical institutional ethnography (CIE) combines Dorothy Smith's institutional ethnography with an explicit critical theory lens to investigate how ruling relations, texts, and institutional discourses reproduce inequality and power asymmetries. Starting from the lived experiences of people positioned within or subordinated by institutions, CIE traces how abstract institutional processes coordinate everyday life and subjects those processes to normative critique aimed at social transformation.

Interviews, documents, observations, institutional texts

Smith, D. E. (2005). Institutional Ethnography: A Sociology for People. AltaMira Press.

Smith, D. E. (Ed.). (2006). Institutional Ethnography as Practice. Rowman & Littlefield.

institutional-ethnography critical-ethnography ethnography critical-discourse-analysis critical-case-study grounded-theory


Critical IPA
CIPA
critical-lens IPA
critical interpretive phenomenology

1996 (IPA); critical variant explicitly theorised in the 2000s–2010s

Jonathan A. Smith (IPA); critical extension developed within the IPA tradition by Smith, Flowers, Larkin and associated scholars

Critical Interpretative Phenomenological Analysis (Critical IPA) is a qualitative approach that combines the double-hermeneutic interpretive work of standard IPA with an explicit critical lens, examining not only how participants make sense of their experience but also how power, social structures, ideology, and systemic inequalities shape that experience. It retains the ideographic, person-centred rigour of IPA while asking whose interests are served and what is silenced or constrained.

Qualitative research design and analytic approach

In-depth interview transcripts, focus group data, personal documents

Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretative Phenomenological Analysis: Theory, Method and Research. Sage.

Eatough, V., & Smith, J. A. (2017). Interpretative phenomenological analysis. In C. Willig & W. Stainton-Rogers (Eds.), The SAGE Handbook of Qualitative Research in Psychology (2nd ed., pp. 193–209). Sage.


Critical life history research

critical biographical research
critical life history
critical life history method
critical biographical inquiry

Ivor Goodson; influenced by critical theory traditions (Freire, Habermas, feminist scholars)

Critical life history research combines the biographical depth of life history methodology with critical theory perspectives — drawing on feminist, Marxist, postcolonial, or critical race frameworks — to examine how structural power relations, social inequalities, and institutional forces shape individual lives. Rather than treating a life story as a purely personal account, this approach reads it as evidence of wider social and political conditions, using individual narratives to surface systemic patterns of oppression, resistance, and agency.

In-depth biographical interviews, personal documents, life narratives

Goodson, I. F., & Sikes, P. (2001). Life History Research in Educational Settings: Learning from Lives. Open University Press.

Weis, L., & Fine, M. (Eds.). (2004). Working Method: Research and Social Justice. Routledge.

life-history-research biographical-research narrative-inquiry critical-narrative-inquiry oral-history critical-ethnography


Critical Metaphor Analysis

CMA
critical metaphor research
corpus-based critical metaphor analysis
ideological metaphor analysis

Critical Metaphor Analysis (CMA) is a qualitative method for uncovering how metaphorical language constructs, legitimises, or contests power relations and ideological positions in texts. Developed by Jonathan Charteris-Black (2004), it integrates Conceptual Metaphor Theory with the evaluative concerns of Critical Discourse Analysis to reveal the persuasive and ideological work performed by metaphors in political, institutional, and media discourse.

Spoken and written texts (political speeches, media, interviews, institutional documents)

Charteris-Black, J. (2004). Corpus Approaches to Critical Metaphor Analysis. Palgrave Macmillan.

Charteris-Black, J. (2011). Politicians and Rhetoric: The Persuasive Power of Metaphor (2nd ed.). Palgrave Macmillan.

interpretive-metaphor-analysis critical-discourse-analysis interpretive-discourse-analysis comparative-metaphor-analysis critical-content-analysis critical-thematic-analysis


Critical Narrative Inquiry

CNI
critical narrative research
critical narrative analysis
narrative inquiry with critical lens

Synthesises D. Jean Clandinin & F. Michael Connelly (narrative inquiry) with critical theory traditions (Kincheloe, McLaren, hooks)

Critical narrative inquiry is a qualitative research approach that collects and analyses personal stories to expose how social structures, power relations, and systemic inequities shape individual experience. It merges the interpretive richness of narrative inquiry with the emancipatory commitments of critical theory, asking not only what happened in a life but also why — and whose interests are served by dominant stories remaining untold or unquestioned.

Personal narratives, life stories, interviews, field texts

Clandinin, D. J., & Connelly, F. M. (2000). Narrative Inquiry: Experience and Story in Qualitative Research. Jossey-Bass.

Kincheloe, J. L., & McLaren, P. (2002). Rethinking Critical Theory and Qualitative Research. In Y. Zou & E. T. Trueba (Eds.), Ethnography and Schools: Qualitative Approaches to the Study of Education (pp. 87–138). Rowman & Littlefield.

narrative-inquiry critical-ethnography critical-discourse-analysis critical-phenomenology interpretive-narrative-inquiry critical-case-study


Critical Netnography

critical online ethnography
critical internet ethnography
critical digital netnography
netnography with critical theory

Late 1990s–2000s (netnography); critical applications prominent from 2000s onward

Robert V. Kozinets (netnography); critical strand developed through integration with critical theory traditions (e.g., critical race theory, feminist theory)

Critical netnography applies the ethnographic toolkit of netnography to online communities while foregrounding a critical theoretical lens — such as critical race theory, feminist theory, or postcolonial theory. Rather than merely describing online culture, it interrogates how power, inequality, and ideology operate within and through digital spaces, making the approach particularly suited to researchers who wish to both understand online life and challenge the social conditions it reflects.

Online community data: posts, threads, comments, profiles, multimedia (text-primary)

Kozinets, R. V. (2020). Netnography: The Essential Guide to Qualitative Social Media Research (3rd ed.). Sage.

Kulavuz-Onal, D., & Vásquez, C. (2013). Reconceptualising fieldwork in a netnography of an online community of English language teachers. Ethnography and Education, 8(2), 224–238.

netnography critical-ethnography critical-discourse-analysis digital-ethnography interpretive-netnography critical-content-analysis


Critical oral history

critical oral inquiry
critical oral testimony research
critical oral narrative research
COH

1970s–1990s (critical turn within oral history)

Alessandro Portelli; also Ronald Grele and the broader oral history movement

Critical oral history applies a critical theory lens to the collection and analysis of first-person spoken accounts of lived experience. It goes beyond preserving personal memory to interrogate how power, identity, race, class, gender, and structural inequality shape what is remembered, what is silenced, and how stories are told. Originating in the work of Alessandro Portelli and the critical turn in oral history from the 1970s onward, the approach treats oral testimony not simply as evidence of the past but as a site of meaning-making and political contestation.

In-depth recorded oral testimonies, life stories, interview transcripts

Portelli, A. (1991). The Death of Luigi Trastulli and Other Stories: Form and Meaning in Oral History. State University of New York Press.

Perks, R., & Thomson, A. (Eds.). (2016). The Oral History Reader (3rd ed.). Routledge.

oral-history critical-narrative-inquiry critical-biographical-research critical-ethnography narrative-inquiry critical-discourse-analysis


Critical phenomenology

critical-phenomenological inquiry
critical-phenomenological analysis
phenomenology and critical theory
politically engaged phenomenology

Late 20th–early 21st century (fully articulated ~2000s–2010s)

Lisa Guenther, Gayle Salamon, Alia Al-Saji (among others); draws on Husserl, Heidegger, Merleau-Ponty, and Frankfurt School critical theory

Critical phenomenology is a qualitative research approach that merges classical phenomenological methods with critical theory to examine how structural forces — race, gender, class, disability, and other axes of power — shape and constrain lived experience. Rather than pursuing neutral description of universal essences, it asks whose experiences are centred, whose are marginalised, and how oppressive social structures are reproduced in the body and in everyday life. It has been consolidated as a distinct field by scholars such as Lisa Guenther, Gayle Salamon, and Alia Al-Saji.

Qualitative research approach — interpretive and emancipatory

In-depth interviews, focus groups, autobiographical accounts, field observations (text data)

Guenther, L. (2020). Critical phenomenology. In G. Weiss, A. V. Murphy, & G. Salamon (Eds.), 50 Concepts for a Critical Phenomenology (pp. 11–16). Northwestern University Press.

Salamon, G. (2018). The Life of the Body: Phenomenology and Ethics. Columbia University Press.

phenomenology hermeneutic-phenomenology interpretive-phenomenology critical-ethnography critical-discourse-analysis participatory-phenomenology


Critical Power (Monod)

Critical Power Model and Anaerobic Work Capacity Assessment

CP model
power-duration relationship
anaerobic capacity
critical torque

Critical power (CP) is the highest power output that can be sustained indefinitely without fatigue, representing the boundary between sustainable and unsustainable exercise. Introduced by Henry Monod and Scherrer in 1965, the critical power model describes the hyperbolic relationship between power output and time-to-exhaustion. The model partitions work capacity into two components: critical power (the aerobic ceiling) and anaerobic work capacity (the maximal work that can be performed above critical power before depletion). This framework is widely used in exercise physiology, sports science, and occupational biomechanics.

Monod, H., & Scherrer, J. (1965). The work capacity of a synergic muscular group. Ergonomics, 8(3), 329-338.

Morton, R. H. (1996). A 3-parameter critical power model. Ergonomics, 39(4), 611-619.

Vandenbossche, J. (2009). The three-parameter critical power function and parameter estimation from maximal efforts. Journal of Sports Sciences, 27(8), 855-863.

lactate-threshold vo2-max respiratory-exchange-ratio session-rpe heart-rate-recovery


Critical Program Evaluation

1970s–1990s (deliberative democratic strand formalised ~1999; transformative paradigm ~2009)

Ernest House, Ken Howe, Donna Mertens (transformative/deliberative democratic evaluation traditions)

Critical program evaluation is an approach to assessing programs that integrates critical theory with standard evaluation methods. It moves beyond measuring whether a program met its stated objectives to interrogating whose interests the program serves, how power and privilege shape its design and outcomes, and whether it advances or hinders equity and social justice. The approach draws on deliberative democratic evaluation (House and Howe) and the transformative paradigm (Mertens), treating evaluation as an inherently value-laden, politically situated practice.

Interviews, focus groups, documents, observations, stakeholder feedback

Mertens, D. M. (2009). Transformative Research and Evaluation. Guilford Press.

House, E. R., & Howe, K. R. (1999). Values in Evaluation and Social Research. Sage Publications.

program-evaluation participatory-program-evaluation educational-action-research critical-educational-action-research evaluation-focused-program-evaluation empowerment-evaluation


Critical Semiotic Analysis

CSA
critical semiotics
critical sign analysis
ideological semiotic analysis

1957 (Barthes); systematised as critical approach in 1980s–1990s

Roland Barthes (mythologies/ideology in signs); extended by Gunther Kress and Theo van Leeuwen (social semiotics)

Critical semiotic analysis is a qualitative method that examines how signs — words, images, gestures, sounds — construct and naturalise ideological meanings. Drawing on Roland Barthes's distinction between denotation and connotation, and on critical social semiotics developed by Kress and van Leeuwen, the approach moves beyond surface-level description to expose how texts reproduce or challenge power relations, cultural norms, and dominant ideologies.

Texts, images, advertisements, media artefacts, multimodal documents

Kress, G., & van Leeuwen, T. (2006). Reading Images: The Grammar of Visual Design (2nd ed.). Routledge.

Barthes, R. (1972). Mythologies (A. Lavers, Trans.). Hill and Wang. (Original work published 1957)

semiotic-analysis critical-discourse-analysis critical-content-analysis discourse-analysis visual-analysis critical-visual-analysis


Critical single case study

critical case study
critical-theory case study
single critical case
CSCS

1984 (Yin's foundational text); critical framing developed through 1990s–2000s

Robert K. Yin (case study design); Bent Flyvbjerg (critical case logic); critical theory influence from Max Horkheimer and Frankfurt School

A critical single case study is a qualitative research design that investigates one bounded, strategically selected case through a critical-theory lens, aiming not only to understand the case in depth but also to expose underlying power relations, structural inequalities, or ideological conditions that shape the phenomenon. It combines the analytic depth of single-case inquiry with the emancipatory agenda of critical social science.

Interviews, documents, observations, artefacts (text and field data)

Flyvbjerg, B. (2006). Five misunderstandings about case-study research. Qualitative Inquiry, 12(2), 219–245.

Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage.

critical-multiple-case-study critical-case-study interpretive-single-case-study critical-ethnography critical-discourse-analysis critical-grounded-theory


Critical Straussian Grounded Theory

critical GT (Straussian)
critical Strauss-Corbin grounded theory
critical systematic grounded theory

1990s (Straussian GT); critical synthesis from 2000s onward

Anselm Strauss & Juliet Corbin (Straussian base); critical integration draws on critical theory traditions (e.g., Kincheloe, Denzin)

Critical Straussian Grounded Theory combines the systematic coding procedures of Strauss and Corbin's grounded theory — open, axial, and selective coding leading to a paradigm model — with a critical theoretical stance that foregrounds power, inequality, and social structure. The researcher does not merely describe a social process but interrogates the conditions that produce and sustain it, connecting emergent theory to broader structures of domination or marginalization.

Interviews, observations, documents (text data)

Strauss, A., & Corbin, J. (1990). Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Sage.

Kincheloe, J. L., & Tobin, K. (2009). The much exaggerated death of positivism. Cultural Studies of Science Education, 4(3), 513–528.

straussian-grounded-theory critical-grounded-theory critical-constructivist-grounded-theory critical-classic-grounded-theory grounded-theory critical-qualitative-content-analysis


Critical Thematic Analysis

CTA
critical-theoretic thematic analysis
thematic analysis with critical lens
critical qualitative thematic inquiry

2000s–2010s (consolidation as named variant)

Draws on Virginia Braun & Victoria Clarke (thematic analysis, 2006) combined with critical theory traditions (Frankfurt School, feminist and postcolonial theorists)

Critical thematic analysis (CTA) is a qualitative approach that combines the systematic coding procedures of Braun and Clarke's thematic analysis with the interrogative stance of critical theory. Rather than merely describing patterns in data, CTA asks whose interests those patterns serve, what power relations they reflect, and what is absent or silenced. It is used to surface ideology, structural inequality, and hegemonic assumptions embedded in participants' accounts or in texts.

Interview transcripts, focus group data, documents, media texts

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.

Rice, C., & Mündel, I. (2018). Story-making as methodology: Disrupting dominant stories through multimedia knowledge translation. Canadian Review of Sociology, 55(2), 211–231. [Critical thematic analysis applied in disability and feminist contexts; see also Rice, C. et al. for critical qualitative praxis.]

thematic-analysis critical-discourse-analysis reflexive-thematic-analysis critical-qualitative-content-analysis critical-narrative-inquiry feminist-research


Critical Thinking Dispositions Scale

Cognitive dispositions and habits of mind

The Critical Thinking Dispositions Scale (CTDS), exemplified by the California Critical Thinking Disposition Inventory (CCTDI), measures the extent to which individuals exhibit cognitive dispositions conducive to critical thinking. Developed by Facione (1992), it assesses dimensions including truth-seeking, open-mindedness, analytical orientation, self-confidence, systematic approach, and inquisitiveness. Critical thinking dispositions—the habits of mind and values that support rigorous reasoning—are distinct from but complementary to critical thinking skills.

Critical thinking propensity measurement

Facione, P. A., Facione, N. C., & Giancarlo, C. A. F. (1992). The California Critical Thinking Disposition Inventory. Insight Assessment, Millbrae, CA.

Facione, P. A. (2000). The Disposition Toward Critical Thinking: Its Character, Measurement, and Relationship to Critical Thinking Skill. Informal Logic, 20(1), 61-84.

study-process-questionnaire academic-self-efficacy-scale course-experience-questionnaire student-engagement-scale


Criticality Safety Analysis

Criticality Safety Analysis and Chain Reaction Control

nuclear safety assessment
chain reaction analysis
fissile material control

Criticality safety analysis is a systematic evaluation of fissile material systems to ensure nuclear chain reactions remain controlled, originating from Hahn and Strassmann's 1938 discovery of nuclear fission. It determines safe limits on fissile mass, concentration, geometry, and spacing using neutron transport calculations and experimental validation to prevent uncontrolled nuclear excursions in storage, processing, and transportation.

American National Standards Institute (2019). Nuclear Criticality Safety in Operations with Fissionable Material Outside Reactors. ANSI/ANS-8.1-19.40.

Paxton, H. C., & Pruvost, N. L. (1990). Critical Dimensions of Systems Containing U-235, Pu-239, and U-233. LA-10860-MS, Los Alamos National Laboratory.

neutron-transport-calculation monte-carlo-neutron-particle nuclear-decay-analysis radiation-dose-assessment reactor-kinetics


Cronbach's Alpha

Cronbach's Alpha Reliability Coefficient

coefficient alpha
alpha reliability
internal consistency reliability
Güvenilirlik Analizi (Cronbach Alpha)

Cronbach's alpha is a coefficient of internal consistency that quantifies the degree to which a set of items on a scale measures the same underlying construct. Introduced by Lee J. Cronbach in 1951, it remains the most widely reported reliability index in social-science, health, and educational research.

Reliability / internal consistency coefficient

α ≥ 0.70 acceptable; ≥ 0.80 good; ≥ 0.90 excellent

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.

Nunnally, J. C. & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). McGraw-Hill.

exploratory-factor-analysis confirmatory-factor-analysis mcdonalds-omega sem pca


Crop Growth Model

Decision Support System for Agrotechnology Transfer (DSSAT) / Agricultural Production Systems Simulator (APSIM)

James W. Jones, Gerbrand T. Hoogenboom (DSSAT); Brian A. Keating, Peter S. Carberry (APSIM)

Crop growth models are mechanistic simulation systems designed to predict crop development, biomass accumulation, and yield under varying environmental and management conditions. DSSAT (Decision Support System for Agrotechnology Transfer) and APSIM (Agricultural Production Systems Simulator) are the most widely used platforms, developed in the 1990s-2000s to support agronomic decision-making and climate adaptation research.

Jones, J. W., Hoogenboom, G., Porter, C. H., et al. (2003). The DSSAT cropping system model. European Journal of Agronomy, 18(3-4), 235-265.

Keating, B. A., Carberry, P. S., Hammer, G. L., et al. (2003). An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy, 18(3-4), 267-288.

Passioura, J. B. (1996). Simulation models: science, snake oil, education, or engineering? Agronomy Journal, 88(5), 690-694.


Crop Growth Simulation

Crop phenological model
Growth stage simulation

Crop Growth Simulation is a computational pipeline for predicting daily or seasonal crop development, biomass accumulation, and yield under varying environmental conditions. Developed by Jones and colleagues in the DSSAT framework, this method integrates agronomic knowledge with process-based modeling to enable decision support in field management.

Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Basso, B., Hunt, L. A., ... & Winter, S. R. (2003). The DSSAT cropping system model. European journal of agronomy, 18(3-4), 235-265.

Sinclair, T. R., & Seligman, N. G. (1996). Crop modeling: From infancy to maturity. Agronomy journal, 88(5), 698-704.

irrigation-scheduling-etref nitrogen-use-efficiency crop-yield-estimation phenological-observation precision-agriculture-ndvi


Crop Load Management

Quantitative Optimization of Fruit Number and Size Through Thinning and Load Balancing

fruit thinning
load balancing
fruit density regulation

Fruit development and quality optimization

Crop load management uses quantitative assessment of fruit number and tree vigor to optimize yields and fruit quality through selective thinning and load balancing. This method combines visual assessment of fruitlet density, calculation of target fruit number based on tree age and vigor, physical or chemical thinning, and yield monitoring to achieve the optimal balance between productivity and fruit size and flavor.

Ackley, W. B., & Wattendorf, R. J. (1962). The relationship of crop load to yield, fruit quality, and return bloom in apples. Proceedings of the American Society for Horticultural Science, 80, 73–83.

Wagenmakers, P. S., Callesen, O., & Goulding, K. (2001). Nutrient management of apple orchards in Northern Europe. Horticultural Reviews, 27, 1–64.

pollination-efficiency pruning-response-analysis postharvest-storage-simulation ripeness-index


Crop Yield Estimation

Pre-Harvest Yield Prediction and Harvest Monitoring

Yield forecasting
Harvest prediction
Yield monitoring

Agronomic research institutions (CIMMYT, ICRISAT, IRRI)

Crop Yield Estimation is an analytical and predictive pipeline for forecasting final crop yield before harvest or monitoring yield accumulation during the growing season. Developed by agronomic research centers (CIMMYT, ICRISAT, IRRI), this method combines field observations, environmental data, and statistical models to predict grain or biomass output, informing harvest planning, market decisions, and performance evaluation.

Lobell, D. B., Thau, D., Seifert, C., Engle, E., & Shadow, B. (2015). A regional crop yield forecasting system for Sub-Saharan Africa. Global Food Security, 5, 6-15.

Egli, D. B. (2010). Seed biology and the yield of grain crops (2nd ed.). CABI Publishing, Wallingford, UK.

crop-growth-simulation precision-agriculture-ndvi phenological-observation nitrogen-use-efficiency irrigation-scheduling-etref


Cross-Cultural Competence Inventory

The Cross-Cultural Competence Inventory (CCCI) is a comprehensive self-report measure designed to assess healthcare providers' competence in delivering culturally sensitive care across diverse populations. The CCCI evaluates multiple dimensions of cross-cultural competence, including cultural awareness, knowledge of diverse health beliefs, communication skills, and the ability to adapt interventions to cultural contexts. Used in nursing, medicine, and allied health programs, the CCCI supports both individual assessment and organizational quality improvement initiatives.

Moore, J. A., & Mercado, D. (2005). Cross-cultural competence development in healthcare professions. Journal of Nursing Education, 44(7), 313–321.


Cross-Docking

Cross-docking is a logistics strategy in which products arriving at a distribution center from suppliers are unloaded, sorted, consolidated, and immediately reloaded onto outbound vehicles destined for customers, with minimal or no storage time. Rather than storing inventory in a warehouse, products flow through in 24–48 hours. Cross-docking reduces inventory holding costs, improves product freshness, and increases throughput of the distribution network. It is widely used in fast-moving consumer goods, parcel delivery, and retail supply chains.

Apuzzio, M. (2008). Essentials of supply chain management. New Jersey: Pearson Education.

Gue, K. R., & Kang, Y. (2007). Staging queues revisited. Manufacturing & Service Operations Management, 9(1), 100-112.

inventory-routing scor-model facility-layout aggregate-planning vendor-managed-inventory


Cross-Document Entity Tracking

Cross-Document Entity Coreference Resolution and Tracking

cross-document coreference resolution
cross-doc entity linking
Belge Ötesi Varlık Takibi

1998 (scoring foundations); 2019 (neural joint model)

Cross-document entity tracking, formally known as cross-document coreference resolution, identifies and merges all references to the same real-world entity scattered across a collection of documents. Rooted in the B3 evaluation framework introduced by Bagga and Baldwin (1998) and substantially advanced by the neural joint model of Barhom et al. (2019), the method builds entity clusters that span document boundaries — enabling multi-document understanding, knowledge-base population, and corpus-wide entity analysis.

Bagga & Baldwin (1998); Barhom et al. (2019)

NLP pipeline — cross-document coreference resolution

Input: A defined set of text documents with completed NER and within-document entity linking

Output: Clusters of entity mentions that refer to the same real-world entity across documents

Bagga, A. & Baldwin, B. (1998). Algorithms for Scoring Coreference Chains. In Proceedings of the LREC 1998 Linguistic Coreference Workshop, pp. 563–566.

Barhom, S., Shwartz, V., Eirew, A., Bugert, M., Reimers, N. & Dagan, I. (2019). Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), pp. 4179–4189.

named-entity-recognition coreference-resolution entity-linking information-extraction knowledge-graph-construction


Cross-lingual Text Analysis

Cross-lingual Text Analysis (Multilingual Representation Learning)

multilingual text analysis
cross-lingual representation learning
Çok Dilli Metin Analizi (Cross-lingual)

Cross-lingual text analysis lets you compare and analyse texts written in different languages within a shared vector space. Building on multilingual representation learning surveyed by Conneau et al. (2020) and Pires et al. (2019), it maps documents from several languages into one common embedding space so multilingual corpora can be studied together.

Multilingual transformers (mBERT, XLM-R)

Output: Shared cross-lingual vector space for comparison and analysis

Conneau, A. et al. (2020). Unsupervised Cross-lingual Representation Learning at Scale. Proceedings of ACL.

Pires, T., Schlinger, E. & Garrette, D. (2019). How Multilingual is Multilingual BERT? Proceedings of ACL.

bert-embeddings sentiment-analysis text-classification topic-modeling


Cross-Quantilogram

The cross-quantilogram extends the cross-correlogram concept to quantile pairs of two time series, measuring dependence at different quantile levels. Introduced by Linton and Whang (2012), it captures how shocks at specific quantile levels in one series relate to movements in another, enabling asymmetric dependence analysis. This approach is particularly valuable when downside and upside risk correlations differ materially.

Linton, O., & Whang, Y. J. (2012). Quantile comparisons of time series data. Journal of Econometrics, 170(2), 242-257.

Kılıç, R., & Pohlmann, T. (2011). Directional spillover effects in international equity markets. Journal of Banking & Finance, 35(9), 2351-2361.


Cross-sectional Causal-Comparative Research Design

cross-sectional ex post facto design
single-wave causal-comparative study
cross-sectional group-comparison design
cross-sectional criterion-group study

Donald T. Campbell and Julian C. Stanley (quasi-experimental foundations); refined in education research by various methodologists

Cross-sectional causal-comparative research compares two or more pre-existing groups — defined by a characteristic or experience that has already occurred — on one or more outcome variables, with all data collected at a single point in time. Because the presumed cause (group membership) precedes measurement but cannot be manipulated, the design sits between purely descriptive and truly experimental work. It is widely used in education, psychology, and social sciences when randomization is impossible or unethical.

Numeric group-level data collected at a single time point; existing categorical grouping variable (cause) precedes measurement

Frankfort-Nachmias, C., & Nachmias, D. (2015). Research Methods in the Social Sciences (8th ed.). Worth Publishers.

Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage Publications.


Cross-sectional Descriptive Research

Cross-sectional Descriptive Research Design

cross-sectional survey
descriptive cross-sectional study
prevalence study
one-shot descriptive survey

Mid-20th century (1950s–1970s, widespread codification)

Rooted in survey methodology traditions; formalized in epidemiology and social science research design texts of the mid-20th century

Cross-sectional descriptive research collects data from a population or sample at a single point in time to portray the current distribution of characteristics, attitudes, behaviors, or conditions. It answers 'what is happening now?' questions without manipulating variables or following participants over time. Widely used in epidemiology, education, psychology, and the social sciences, it is the foundation for prevalence estimates, needs assessments, and baseline profiling.

Quantitative observational research design

Questionnaires, structured interviews, administrative records, or standardized assessments collected at a single point in time

Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage.

Kesmodel, U. S. (2018). Cross-sectional studies — what are they good for? Acta Obstetricia et Gynecologica Scandinavica, 97(4), 388–393.

survey-research descriptive-research correlational-research longitudinal-research cohort-research observational-quantitative-research


Cross-sectional epidemiological study

Cross-sectional Epidemiological Study Design

prevalence study
cross-sectional survey
transversal study
cross-sectional design

1960s (formal codification); widely practiced since mid-20th century

Classical epidemiology tradition; systematized by Brian MacMahon and Thomas Pugh (1960s)

A cross-sectional epidemiological study measures the exposure(s) and outcome(s) of interest simultaneously in a defined population at a single point in time (or over a short period). Because there is no follow-up, it is the most efficient observational design for estimating disease prevalence and for generating hypotheses about associations between risk factors and health outcomes.

Observational, descriptive/analytic epidemiological design

Survey data, clinical records, administrative data — measured at a single point in time

Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press.

cohort-study case-control-study ecological-study diagnostic-accuracy-study screening-test-evaluation randomized-clinical-trial


Cross-sectional ex post facto design

Cross-sectional Ex Post Facto Research Design

Fred N. Kerlinger (formalized ex post facto methodology)

A cross-sectional ex post facto design investigates presumed causal relationships by comparing groups that already differ on a key characteristic — all measured at a single point in time. Because the independent variable (e.g., smoking history, prior educational attainment) has already occurred and cannot be manipulated, the researcher works backward from observed outcomes to infer probable antecedents. It is widely used in education, public health, and the social sciences when experimental control is ethically or practically impossible.

Non-experimental quantitative research design

Numerical and categorical data collected at a single time point; pre-existing group differences

Kerlinger, F. N. (1973). Foundations of Behavioral Research (2nd ed.). Holt, Rinehart and Winston.

Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2009). How to Design and Evaluate Research in Education (7th ed.). McGraw-Hill.


Cross-sectional Quantitative Content Analysis

CS-QCA
cross-sectional content analysis
single-timepoint content analysis
quantitative media content analysis

Mid-20th century (formalized 1952–2000s)

Berelson, B.; Krippendorff, K.; Neuendorf, K. A.

Cross-sectional quantitative content analysis is an observational research design in which a systematically drawn sample of communicative content — news articles, social media posts, advertisements, or other symbolic material — is collected at a single point in time and coded using pre-defined numerical categories to describe or test hypotheses about patterns, frequencies, or associations within that content.

Text, images, audio, video, or other symbolic content sampled at a single time point

Neuendorf, K. A. (2002). The Content Analysis Guidebook. Sage Publications.

Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology (2nd ed.). Sage Publications.


Cross-sectional relational survey

Cross-sectional Relational Survey Research

cross-sectional correlational survey
one-time relational survey
cross-sectional associational survey
single-occasion relational survey

Rooted in survey methodology traditions; codified by Fraenkel, Wallen, and Creswell among others

A cross-sectional relational survey collects data from a representative sample at a single point in time and examines the statistical relationships (correlations, associations, predictions) among two or more variables. It combines the temporal efficiency of cross-sectional design with the relational focus of correlational survey research, making it one of the most widely used quantitative designs in education, social science, and health research when a quick, population-level picture of variable relationships is needed.

Quantitative survey scores, Likert-scale and continuous variables

Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to Design and Evaluate Research in Education (8th ed.). McGraw-Hill.

correlational-research cross-sectional-research relational-survey survey-research descriptive-research longitudinal-correlational-research


Cross-Sectional Study Design

Cross-Sectional Survey or Prevalence Study

prevalence study
cross-sectional survey
snapshot study
survey design

Epidemiologists in the mid-20th century; formalized by Kelsey, Rothman, and others

A cross-sectional study (or prevalence study) measures exposure and outcome simultaneously at a single point in time, producing a 'snapshot' of a population. Respondents are recruited and surveyed (or examined) on the same occasion, capturing current prevalence of both exposure and disease. Cross-sectional studies are simple, quick, and inexpensive, making them popular for needs assessments, surveillance, and generating hypotheses—though they cannot establish causality due to lack of temporal sequence.

Rothman, K. J., Lash, T. L., & Greenland, S. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins.

Lynn, P. (2009). Methodology of longitudinal surveys. Wiley Interdisciplinary Reviews: Computational Statistics, 1(3), 369–379.

cohort-study-design case-control-study-design prevalence survey-design confounding-bias


Cross-sectional survey research

cross-sectional survey
single-occasion survey
prevalence survey design
snapshot survey

1930s–1950s (formalized with large-scale opinion and health surveys)

Established through the social survey tradition (Bowley, Gallup, and others in the early-to-mid 20th century)

Cross-sectional survey research administers a structured questionnaire or interview to a representative sample of a population at one point in time. It is the workhorse design for estimating prevalence, describing group characteristics, and mapping associations among variables across a wide range of disciplines — from public health and education to marketing and political science.

Questionnaire or structured interview data collected from a sample at a single point in time

Fowler, F. J. (2009). Survey Research Methods (4th ed.). Sage Publications.

survey-research cross-sectional-research descriptive-research correlational-research longitudinal-survey-research relational-survey


Cross-tabulation analysis

Cross-tabulation Analysis (Contingency Table Analysis)

crosstab
contingency table analysis
two-way frequency table
bivariate frequency analysis

Cross-tabulation analysis (contingency table analysis) is a foundational descriptive and inferential technique for examining the relationship between two or more categorical variables. It arranges observed frequencies into a table of rows and columns, enabling visual inspection of patterns and formal chi-square testing of independence between the variables.

Descriptive and inferential categorical analysis

Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157–175.

Agresti, A. (2002). Categorical Data Analysis (2nd ed.). Wiley-Interscience.

chi-square-test fishers-exact-test frequency-analysis logistic-regression cramers-v odds-ratio


CROSS-VALIDATION

CROSS-VALIDATION (Cross-Validation — k-fold hold-out validation of MCDM decision consistency) is a ranking multi-criteria decision-making (MCDM) method introduced by Stone, M. in 1974. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Robustness wrapper — k-fold cross-validation for MCDM stability

Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society Series B


Cross-Wavelet Transform

The cross-wavelet transform (XWT) is a bivariate extension of the continuous wavelet transform that measures the joint time-frequency representation of two signals. Introduced by Torrence and Compo (1998) and applied extensively by Grinsted, Moore, and Jevrejeva (2004) to geophysical data, XWT reveals where two signals share common spectral power and the phase relationship between them at each time-frequency point. This is the natural generalization of classical cross-spectral analysis to the time-varying domain.

Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79(1), 61–78.

Torrence, C., & Webster, P. J. (1999). Interdecadal changes in the ENSO–monsoon system. Journal of Climate, 12(8), 2679–2690.

Grinsted, A., Moore, J. C., & Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11(5–6), 561–566.

continuous-wavelet-transform wavelet-coherence cross-correlation fourier-analysis


Crossformer

Crossformer (Cross-Dimension Dependency Transformer)

Cross-Dimension Dependency Transformer
Crossformer TSF
Çapraz-Boyut Bağımlılık Transformatörü

Crossformer is a Transformer-based architecture for multivariate time series forecasting, introduced by Yunhao Zhang and Junchi Yan at ICLR 2023. Unlike earlier Transformer variants that treat each variate independently, Crossformer explicitly models cross-dimension dependencies alongside temporal patterns. It achieves this through a two-stage attention design — cross-time and cross-dimension — applied over segment-level embeddings organized in a hierarchical encoder, enabling the model to capture both intra-variate dynamics and inter-variate correlations simultaneously.

Transformer-based multivariate time-series forecasting model

Both time and dimension (cross-time and cross-dimension)

Zhang, Y., & Yan, J. (2023). Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting. ICLR.


Crossover A/B Test

within-subject A/B test
crossover split test
repeated-measures A/B test
AB crossover experiment

1949 (crossover design); 2000s (online A/B application)

Crossover design: E. J. Williams (1949); A/B testing framework: Ronald Fisher (experimental roots); modern online application widely attributed to Google and Microsoft experimentation teams

A crossover A/B test is an experimental design in which the same participants or units are exposed to both treatment A and treatment B in sequence, with each serving as their own control. By eliminating between-subject variability, the design achieves higher statistical power than a standard parallel A/B test at the same sample size, but it requires careful handling of carryover effects and time-period confounds.

Continuous, binary, or count outcome data measured on the same units across periods

Jones, B., & Kenward, M. G. (2014). Design and Analysis of Cross-Over Trials (3rd ed.). Chapman and Hall/CRC.

Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press.

ab-design crossover-randomized-controlled-trial multi-arm-experiment adaptive-ab-test factorial-ab-test blocked-ab-test


Crossover ABAB Design

ABAB reversal design
reversal design
withdrawal design
ABAB single-subject design

Murray Sidman and colleagues in applied behavior analysis

The crossover ABAB design is a single-subject experimental design that alternates between baseline (A) and intervention (B) conditions twice within the same participant. By withdrawing and reintroducing the treatment, the researcher can demonstrate experimental control: if behavior improves with B and reverts with A, the causal link between the intervention and the outcome is established without a separate control group.

Repeated measures of behavior over time (continuous observation or interval recording)

Barlow, D. H., Nock, M. K., & Hersen, M. (2009). Single Case Experimental Designs: Strategies for Studying Behavior Change (3rd ed.). Pearson.

Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied Behavior Analysis (3rd ed.). Pearson.

single-subject-design multiple-baseline-design alternating-treatments-design randomized-controlled-trial within-subjects-design reversal-design


Crossover Adaptive Experiment

adaptive crossover trial
adaptive crossover design
crossover adaptive trial
ACE design

Developed through convergence of crossover trial methodology (Senn, Williams) and adaptive design methods (Bauer, Köhne, Chow, Chang)

An adaptive crossover experiment combines the within-subject efficiency of crossover designs — where each participant receives multiple treatments in sequence — with pre-specified adaptive rules that allow trial parameters to be modified based on interim data. Each participant acts as their own control across treatment periods, while ongoing accumulating evidence can trigger pre-planned changes such as sample size re-estimation, treatment arm dropping, or allocation ratio adjustment, all governed by a formal adaptation plan to preserve inferential validity.

Experimental design — hybrid adaptive/crossover

Continuous, binary, or ordinal outcome measurements; repeated within-subject observations

Chow, S.-C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman & Hall/CRC.

Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). John Wiley & Sons.

crossover-randomized-controlled-trial adaptive-experiment adaptive-randomized-controlled-trial factorial-adaptive-experiment multiple-baseline-design crossover-factorial-experiment


Crossover Control Group Experimental Design

Crossover Experimental Design with Control Group

repeated-measures crossover with control arm

Mid-20th century; systematic treatment from 1980s onward

Established in clinical pharmacology and agricultural research; formalized by B. Jones & M. G. Kenward

A crossover control group experimental design is an experimental approach in which participants are randomly assigned to sequences of conditions that include both a treatment and a control (no-treatment or placebo) period, with each participant experiencing both the experimental and control conditions in succession. By using each participant as their own control across periods, this design sharply reduces between-subject variability and typically requires fewer participants than parallel group trials to achieve equivalent statistical power.

Continuous, ordinal, or binary outcome measurements collected at multiple time points

Jones, B., & Kenward, M. G. (2003). Design and Analysis of Cross-Over Trials (2nd ed.). Chapman and Hall/CRC.

crossover-randomized-controlled-trial crossover-factorial-experiment control-group-experimental-design pretest-posttest-experimental-design ab-design repeated-measures-anova


Crossover Design

within-subject crossover
cross-over design
AB/BA design
Çapraz Desen (Crossover Design)

Early formalized in clinical research literature; widely used since mid-20th century

A crossover design is an experimental design in which each participant receives all treatments under investigation, but in a different sequence and across separate time periods. Each subject thus acts as their own control, which substantially reduces between-subject variability and allows efficient treatment comparisons with smaller sample sizes. The approach has been central to clinical pharmacology and comparative research since the mid-20th century, with foundational methodology codified by Senn (2002) and Jones & Kenward (2014).

AB/BA (two-period) or Williams sequence (multi-treatment)

Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley.

Jones, B. & Kenward, M. G. (2014). Design and Analysis of Cross-Over Trials (3rd ed.). CRC Press.

paired-t-test repeated-measures-anova latin-square-design factorial-design split-plot-design randomized-complete-block


Crossover Factorial Experiment

within-subject factorial design
repeated-measures factorial experiment
factorial crossover trial
crossover factorial trial

1920s–1960s (synthesis of factorial and crossover traditions)

R. A. Fisher (factorial principles, 1920s); crossover integration developed in biostatistics through mid-20th century

A crossover factorial experiment combines two powerful design principles: factorial structure, which studies multiple factors and their interactions simultaneously, and crossover structure, in which each participant receives more than one treatment combination across sequential periods. By serving as their own control, participants reduce between-subject variability, improving statistical power while also revealing how different factor levels interact within the same individual.

Continuous, ordinal, or binary outcome measurements collected at multiple time points per participant

Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley.

crossover-randomized-controlled-trial factorial-experiment factorial-randomized-controlled-trial repeated-measures-anova latin-square-design within-subjects-design


Crossover Field Experiment

within-subject field experiment
crossover field trial
repeated-measures field experiment
field crossover design

1960s–1970s (field experiment framework); crossover application in non-clinical fields from 1980s onward

Crossover design principles attributed to R. A. Fisher (1930s); field experiment tradition developed by Donald T. Campbell and Julian Stanley (1960s)

A crossover field experiment is a within-subject experimental design conducted outside the laboratory in naturalistic, real-world settings. Each participant or unit receives multiple treatments in a randomized sequence, separated by washout periods, allowing researchers to observe causal effects while each unit serves as its own control. This approach combines the internal validity of crossover designs with the ecological validity characteristic of field experimentation.

Within-subject experimental design conducted in naturalistic settings

Continuous, ordinal, or count outcomes measured at multiple time points per participant or unit

Gerber, A. S., & Green, D. P. (2012). Field Experiments: Design, Analysis, and Interpretation. W. W. Norton & Company.

crossover-randomized-controlled-trial field-experiment crossover-laboratory-experiment factorial-field-experiment blocked-field-experiment multiple-baseline-design


Crossover Fractional Factorial Experimental Design

crossover FF design
within-subject fractional factorial
repeated-measures fractional factorial
crossover FFE

1950s–1970s (fractional factorial from 1940s; crossover integration from 1960s–1970s)

Box, Hunter & Hunter (fractional factorial); Senn & Williams (crossover integration)

A crossover fractional factorial experiment is a within-subject design in which each participant receives a strategically chosen subset of all possible factor-level combinations in a defined sequence, with washout periods between treatment periods. By combining the run-economy of fractional factorial designs with the within-subject efficiency of crossover designs, it allows estimation of main effects and selected interactions while controlling for between-subject variability using far fewer participants and experimental runs than a full factorial crossover.

Within-subject multi-factor experimental design

Continuous, ordinal, or binary outcome measurements; repeated measures per subject

Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley.

crossover-randomized-controlled-trial fractional-factorial-experiment full-factorial-experiment factorial-experiment crossover-full-factorial-experiment blocked-fractional-factorial-experiment


Crossover Full Factorial Experiment

Crossover Full Factorial Experimental Design

repeated-measures full factorial experiment

Mid-to-late 20th century (crossover trials formalised ~1960s–1980s; full factorial DoE from Fisher ~1935)

Developed within the design-of-experiments tradition (R. A. Fisher and successors); crossover adaptation formalised by B. Jones and M. G. Kenward

A crossover full factorial experiment combines the efficiency of a crossover (within-subject) design with the comprehensiveness of a full factorial design. Every participant receives all combinations of the factor levels across successive treatment periods, separated by washout intervals, allowing complete estimation of all main effects and interactions while using each participant as their own control.

Within-subject full factorial experimental design

Continuous or ordinal outcome measurements from the same participants across multiple treatment periods

crossover-randomized-controlled-trial full-factorial-experiment factorial-experiment crossover-factorial-experiment repeated-measures-anova latin-square-design


Crossover Laboratory Experiment

Crossover Within-Subjects Laboratory Experiment

within-person laboratory crossover trial

Mid-20th century; consolidated 1980s–2000s

Established in pharmacological and behavioral research; Jones & Kenward formalized the framework

A crossover laboratory experiment is a within-subjects experimental design conducted in a controlled lab environment in which each participant receives two or more treatments sequentially, serving as their own control. By eliminating between-person variability from the error term, it yields high statistical power with relatively small samples. Treatment order is randomized or counterbalanced across participants to guard against order and carryover effects.

Continuous, ordinal, or categorical outcome measurements collected per participant per treatment period

Jones, B., & Kenward, M. G. (2014). Design and Analysis of Cross-Over Trials (3rd ed.). CRC Press.

crossover-randomized-controlled-trial laboratory-experiment factorial-laboratory-experiment repeated-measures-anova within-subjects-design ab-design


Crossover multi-arm experiment

multi-arm crossover trial
multi-period multi-treatment crossover
CMAT
multi-treatment crossover experiment

Mid-20th century; multi-arm extensions formalized by 1970s–1980s

Developed from early crossover trial methodology (Williams 1949; Cochran & Cox 1957)

A crossover multi-arm experiment is a within-subject experimental design in which each participant receives three or more treatments (arms) across successive periods, with random assignment to sequence. Because every participant experiences all arms, the design eliminates between-subject variability from treatment comparisons, dramatically increasing statistical power for a given sample size. It is widely used in clinical pharmacology, psychology, agriculture, and behavioral research.

Within-subject experimental design with multiple treatment arms

Continuous, ordinal, or binary outcome measurements per period per participant

crossover-randomized-controlled-trial multi-arm-experiment factorial-experiment latin-square-design adaptive-experiment repeated-measures-design


Crossover Multiple Baseline Design

Crossover Multiple Baseline Single-Case Experimental Design

CMBD
crossover MBD
multiple baseline crossover design
within-subject multiple baseline design

1968 (multiple baseline origins); crossover extension developed in behavioral and rehabilitation research from the 1980s onward

Derived from Baer, Wolf, and Risley (multiple baseline, 1968) and classical crossover design traditions

The crossover multiple baseline design is a single-case experimental design (SCED) that layers crossover sequencing onto a multiple baseline structure. Across two or more tiers — participants, behaviors, or settings — baselines are staggered in time; then treatments are introduced and later reversed or alternated across tiers, so each tier acts as both a treatment and a control unit. The design provides within-subject replication while controlling for time-related confounds.

Single-case experimental design with crossover sequencing

Repeated measures of a single behavior or outcome over time (continuous or count data)

Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97.

Kazdin, A. E. (2011). Single-Case Research Designs: Methods for Clinical and Applied Settings (2nd ed.). Oxford University Press.

multiple-baseline-design crossover-randomized-controlled-trial ab-design aba-design abab-design single-subject-experimental-design


Crossover Natural Experiment

within-unit natural experiment
reversal natural experiment
crossover quasi-experiment

Crossover designs: mid-20th century; applied to natural experiments: 1990s–2000s

Drawn from crossover trial methods (Jones & Kenward) and natural experiment tradition (Mill, 1843; Dunning, 2012)

A crossover natural experiment exploits an externally imposed condition — a policy change, law, or environmental event — that exposes the same units (individuals, regions, firms) to both treatment and control states at different times. By observing each unit in multiple conditions, researchers use within-unit variation to estimate causal effects without researcher-controlled randomization, combining the internal validity advantage of crossover designs with the real-world relevance of natural experiments.

Panel or longitudinal observational data; policy records; administrative data

Dunning, T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge University Press.

Jones, B., & Kenward, M. G. (2003). Design and Analysis of Cross-Over Trials (2nd ed.). Chapman & Hall/CRC.

crossover-randomized-controlled-trial natural-experiment difference-in-differences crossover-field-experiment interrupted-time-series regression-discontinuity-design


Crossover Pretest-Posttest Experimental Design

within-subjects pretest-posttest design
repeated-measures crossover design
AB/BA pretest-posttest design
crossover repeated-measures design

1963 (Campbell & Stanley framework); crossover methodology formalized 1980s–2000s

Donald T. Campbell & Julian C. Stanley (pretest-posttest framework); Stephen Senn (crossover trial methodology)

A crossover pretest-posttest experimental design is a within-subjects experiment in which each participant receives two or more treatments in a randomized sequence, with outcome measurements taken both before and after each treatment period. By serving as their own control across conditions, participants allow direct intra-individual comparison, dramatically increasing statistical power while reducing the sample size required relative to a parallel-group design.

Continuous or ordinal outcome measurements at pretest and posttest for each treatment period

Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally.


Crossover Randomized Controlled Trial

crossover RCT
crossover trial
within-subject RCT
AB/BA crossover design

1960s (Grizzle 1965 for statistical foundations); widely used in clinical research since the 1970s

Early formalized by statisticians including Bradford Hill and colleagues in clinical trials; theoretical framework developed by Grizzle (1965) and later Senn (2002)

A crossover randomized controlled trial (crossover RCT) is an experimental design in which each participant receives all study interventions in a randomized sequence, separated by a washout period. Because every participant serves as their own control, within-subject variability is eliminated from the treatment comparison, yielding greater statistical power per participant than a parallel-group RCT of equal size.

Continuous, ordinal, or binary outcome measures collected at multiple time points per participant

randomized-controlled-trial factorial-randomized-controlled-trial blocked-randomized-controlled-trial adaptive-randomized-controlled-trial latin-square-design repeated-measures-design


Crossover Single-Subject Experimental Design

crossover SSED
alternating-treatments crossover design
single-case crossover design
N-of-1 crossover design

1970s–1980s (single-case crossover formalized in behavioral research context)

Developed within the single-case research tradition; crossover application formalized by Barlow and Hersen and expanded by Kazdin

The crossover single-subject experimental design (crossover SSED) applies two or more treatment conditions sequentially to the same individual, with a washout or return-to-baseline period between conditions. Because each participant serves as their own control, between-subject variability is eliminated, enabling precise causal inference about treatment effects even with very small samples — often a single participant. This design is widely used in applied behavior analysis, special education, rehabilitation, and clinical psychology.

Repeated behavioral or clinical outcome measures on a single participant or unit

single-subject-experimental-design alternating-treatments-design multiple-baseline-design reversal-aba-design randomized-controlled-trial n-of-1-trial


Crossover Solomon Four-Group Design

Crossover Solomon Four-Group Experimental Design

repeated-measures Solomon four-group design

1949 (base design); crossover adaptation developed through later methodological literature

Richard L. Solomon (base design); crossover extension via repeated-measures methodology

The Crossover Solomon Four-Group Design merges two powerful experimental strategies: the Solomon four-group design's control for pretest sensitization and the crossover design's within-subjects efficiency. Participants are randomly assigned to one of four groups that vary in whether they receive a pretest and in the sequence of treatment and control conditions, allowing the researcher to simultaneously estimate treatment effects, pretest effects, and their interaction while controlling for individual differences through repeated measurement.

Experimental design (pretest-sensitization control + within-subjects crossover)

Continuous or ordinal outcome measures; repeated observations per participant

Solomon, R. L. (1949). An extension of control group design. Psychological Bulletin, 46(2), 137–150.

Braver, M. C. W., & Braver, S. L. (1988). Statistical treatment of the Solomon four-group design: A meta-analytic approach. Psychological Bulletin, 104(1), 150–154.


Croston's Method

Croston's Method for Intermittent Demand Forecasting

Croston Yöntemi — Aralıklı Talep Tahmini

Croston's method, introduced by J. D. Croston in 1972, is a time-series forecasting technique built for intermittent demand series in which periods of zero demand are frequent. Instead of forecasting the raw series, it models the size of demand when it occurs and the interval between demand occurrences as two separate processes.

Intermittent demand time-series forecasting

Separate simple exponential smoothing of demand size and inter-arrival interval

intermittent (count or continuous) demand series

Croston, J. D. (1972). Forecasting and Stock Control for Intermittent Demands. Operational Research Quarterly, 23(3), 289-303.

Syntetos, A. A. & Boylan, J. E. (2005). The Accuracy of Intermittent Demand Estimates. International Journal of Forecasting, 21(2), 303-314.

theta-method exponential-smoothing arima ols-regression poisson-regression


Crown Fire (Van Wagner)

The Van Wagner crown fire model predicts the conditions under which surface fires will transition to active crown fires and the rate of crown fire spread. Developed by Cornelius Van Wagner in the 1970s–1990s, the model is grounded in the physics of heat transfer from the surface flame to the canopy and the rate of vertical flame propagation. The model is used to assess crown fire danger and to guide fuel management decisions in forests with high canopy flammability.

Van Wagner, C. E. (1977). Conditions for the start and spread of crown fire. Canadian Journal of Forest Research, 7(1), 23–34.

Van Wagner, C. E. (1993). Prediction of crown fire behavior in two stands of boreal forest. Canadian Journal of Forest Research, 23(3), 442–449.


CMSD
Crowne-Marlowe Scale
Social Desirability Scale

The Crowne-Marlowe Social Desirability Scale (CMSD) is a 33-item self-report measure designed to assess the tendency to present oneself favorably in social contexts, independent of psychopathology. Developed by Douglas Crowne and David Marlowe in 1960, the CMSD measures impression management and social desirability bias—tendencies that confound responses to personality, health, and behavioral questionnaires. The scale has become the standard reference instrument for detecting and controlling social desirability effects in psychological research.

Social desirability response bias measurement

Crowne, D. P., & Marlowe, D. (1960). A new scale of social desirability independent of psychopathology. Journal of Consulting Psychology, 24(4), 349–354.

Reynolds, W. M. (1982). Development of reliable and valid short forms of the Marlowe-Crowne Social Desirability Scale. Journal of Clinical Psychology, 38(1), 119–125.

Paulhus, D. L. (1991). Measurement and control of response bias. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.), Measures of personality and social psychological attitudes (pp. 17–59). Academic Press.


Cryo-EM Reconstruction

Cryo-Electron Microscopy 3D Reconstruction

cryo-electron microscopy
cryo-EM
single-particle cryo-EM

Cryo-electron microscopy (cryo-EM) determines three-dimensional macromolecular structures at atomic or near-atomic resolution by imaging proteins frozen in vitreous ice. Pioneered by Frank, Henderson, and others, this technique has revolutionized structural biology by enabling visualization of large, non-crystallizable complexes and capturing functional conformational states.

Frank, J. (2002). Single-particle imaging of macromolecules by cryo-electron microscopy. Annual Review of Biophysics and Biomolecular Structure, 31, 303-319.

Henderson, R., Baldwin, J. M., Ceska, T. A., Zemlin, F., Beckmann, E., & Downing, K. H. (1990). Model for the structure of bacteriorhodopsin based on high-resolution electron cryo-microscopy. Journal of Molecular Biology, 213(4), 899-929.

Scheres, S. H. W. (2016). Processing of structurally heterogeneous cryo-EM data in RELION. Methods in Enzymology, 579, 125-157.


Crystal Field Theory

Crystal Field Theory (CFT) is a model that explains the electronic structure, color, magnetism, and reactivity of coordination complexes by considering how the electric field created by surrounding ligands perturbs the d-orbitals of a central metal ion. Developed by Hans Bethe in 1929 and refined throughout the 20th century, CFT is one of the most powerful tools for understanding inorganic chemistry.

Bethe, H. (1929). Termaufspaltung in Kristallen. Annalen der Physik, 3(5), 133–208.

Miessler, G. L., Fischer, P. J., & Tarr, D. A. (2014). Inorganic Chemistry (5th ed.). Pearson.


CS-ARDL

Cross-Sectional Autoregressive Distributed Lag

Panel ARDL with cross-sectional dependence

CS-ARDL (Cross-Sectional ARDL) applies the ARDL framework to panel data while explicitly accounting for cross-sectional dependence—correlation of shocks and relationships across units (countries, firms, regions). Introduced by Pesaran and colleagues (2016), it extends panel ARDL methods to handle common factors or global shocks affecting all units simultaneously. This is crucial for realistic modeling of internationally integrated economies and firm networks.

Pesaran, M. H., & Smith, R. (2016). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6-10), 1089-1117.

Chudik, A., Kapetanios, G., & Pesaran, M. H. (2018). A one covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models. Econometric Reviews, 37(8), 953-1010.


CS-DL

CS-DL (Cross-Sectional Distributed Lag) is a simplified dynamic panel model regressing outcomes on current and lagged explanatory variables without explicit autoregressive terms, while accounting for cross-sectional dependence. Built on Pesaran et al. (2001) and extended by Chudik et al. (2014), it estimates dynamic effects more parsimoniously than ARDL when autocorrelated lags are less critical. This approach is valuable for short-horizon effects and policy impact analysis.

Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships and dynamics. Journal of Applied Econometrics, 16(3), 289-326.

Chudik, A., Kapetanios, G., & Pesaran, M. H. (2014). Common correlated effects estimation in large panels with cross-sectional dependence. Econometric Reviews, 34(6-10), 1078-1088.


CS-NARDL

Cross-Sectional Nonlinear Autoregressive Distributed Lag

CS-NARDL extends the nonlinear autoregressive distributed lag (NARDL) model to panel data, capturing asymmetric long-run and short-run relationships where positive and negative changes in explanatory variables have differential effects. Introduced by Shin et al. (2014) and adapted to panels, it allows studying how cross-sectional units respond differently to positive versus negative shocks while maintaining cointegrating relationships. This approach is essential for understanding economic asymmetries in commodity markets, monetary transmission, and labor markets.

Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a system of nonlinear autoregressive distributed lag equations. Econometric Reviews, 33(1), 56-87.

Wold, E. N., Serrano, G., & Gunnvaldsson, A. (2023). Panel nonlinear ARDL and asymmetric effects. Journal of Econometric Methods, 12(1), 20220039.


CSMA/CA

Carrier Sense Multiple Access with Collision Avoidance

CSMA/CA is a random access protocol for wireless medium access control, designed to enable multiple devices to share a wireless channel while minimizing collisions. Introduced by Phil Karn in 1990, it is the foundation of WiFi (IEEE 802.11) and is now the de facto standard for unlicensed spectrum access. CSMA/CA combines carrier sensing (listen before transmit) with collision avoidance (RTS/CTS handshake) to improve channel efficiency and fairness, avoiding the efficiency loss of pure random access (Aloha).

Karn, P. (1990). MACA—a new channel access method for packet radio. In Proceedings of the ARRL/CRRL Amateur Radio 9th Computer Networking Conference, 134-140.

IEEE 802.11 Working Group. (2020). IEEE Standard for Information Technology—Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. IEEE.


CSTR Model

ideal mixed reactor
back-mix reactor
CSTR

The CSTR (Continuous Stirred-Tank Reactor) model describes the behavior of an ideal mixed reactor where fresh feed is continuously added, products are withdrawn, and contents are kept uniform by vigorous stirring. This fundamental model, formalized by Octave Levenspiel in the 1960s, is widely used to design and scale batch and continuous processes. Despite its simplicity, it captures essential dynamics of industrial reactors and is the baseline for process control and optimization.

Mathematical model for continuous flow reactor

Levenspiel, O. (1999). Chemical Reaction Engineering (3rd ed.). John Wiley & Sons.

Fogler, H. S. (2016). Elements of Chemical Reaction Engineering (5th ed.). Pearson.

Bailey, J. E., & Ollis, D. F. (2004). Biochemical Engineering Fundamentals (2nd ed.). McGraw-Hill.


CT Iterative Reconstruction

Computed Tomography Iterative Reconstruction

MBIR
ASIR
IR-CT
statistical reconstruction

CT Iterative Reconstruction (IR) is a computational technique that reconstructs tomographic images from raw X-ray projection data by iteratively refining an estimate of tissue attenuation until it matches the measured projections. Developed from algebraic reconstruction techniques pioneered by Gordon in 1974, iterative reconstruction has revolutionized clinical CT by enabling high-quality images at reduced radiation dose. Variants such as Adaptive Statistical Iterative Reconstruction (ASIR) and Model-Based Iterative Reconstruction (MBIR) are now standard on modern CT scanners.

Algorithm for tomographic image reconstruction

Gordon, R., Bender, R., Herman, G. T. (1974). Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and X-ray photography. Journal of Theoretical Biology, 29(3), 471-481.

Yu, L., Leng, S., McCollough, C. H. (2012). Iterative reconstruction in medical imaging. Journal of Medical Imaging, 1(3), 033506.

Singh, S., Kalra, M. K., Hsieh, J., et al. (2010). Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. Radiology, 257(2), 373-383.

quantitative-susceptibility-mapping dexa pet-kinetic-modeling dti-tractography radiomics


CTD Profiling

Conductivity-Temperature-Depth (CTD) profiling is the primary method for measuring vertical profiles of seawater properties in oceanography. Developed by Neil Brown in 1977, CTD instruments are equipped with sensors for conductivity, temperature, and pressure (depth), and are typically mounted on water-sampling rosettes. CTD profiling provides essential hydrographic data that characterizes water mass structure, stratification, and circulation patterns.

UNESCO/IOC. (1991). Processing of oceanographic station data. UNESCO Technical Papers in Marine Science, 60.

Roemmich, D., & Gilson, J. (2009). The 2004-2008 global hydrographic climatology. Oceanography, 22(2), 50-61.


CUBIC-EDAS

CUBIC-EDAS (Cubic-EDAS — Cubic Pythagorean Fuzzy EDAS (CuP-EDAS)) is a ranking multi-criteria decision-making (MCDM) method introduced by Paul, T.K., Jana, C., Pal, M. in 2023. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Cubic Pythagorean Fuzzy ranking — CuPyFN = ⟨IvPyFN, PyFN⟩ = (⟨[Y⁻,Y⁺],[F⁻,F⁺]⟩,⟨Y,F⟩); Pythagorean constraint (Y⁺)²+(F⁺)² ≤ 1; average-solution EDAS with score-function PDA/NDA

Paul, T.K., Jana, C., Pal, M. (2023). Multi-criteria group decision-making method in disposal of municipal solid waste based on cubic Pythagorean fuzzy EDAS approach with incomplete weight information. Applied Soft Computing

ahp anp bwm bwm-bayesian ccsd cilos cimas critic


CUBIC-TOPSIS

CUBIC-TOPSIS (Cubic-TOPSIS — Cubic extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Garg, H., Kaur, G. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Cubic Intuitionistic Fuzzy ranking — CIFN = (IVIFN, IFN): interval membership/non-membership ⟨[ζL,ζU],[ϑL,ϑU]⟩ (IVIFS part) + point membership/non-membership ⟨ζ,ϑ⟩ (IFS part); extended TOPSIS with weighted generalised distance

Garg, H., Kaur, G. (2018). Extended TOPSIS method for multi-criteria group decision-making problems under cubic intuitionistic fuzzy environment. Scientia Iranica E


CUBIC-VIKOR

CUBIC-VIKOR (Cubic-VIKOR — Cubic extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Jun, Y. B. Kim, C. S. Yang, K. O. in 2012. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Cubic outranking/ranking — Cubic Fuzzy Set (CuFS: interval [a,b] for internal membership, scalar λ for external)

Jun, Y. B., Kim, C. S., Yang, K. O. (2012). Cubic sets. Annals of Fuzzy Mathematics and Informatics


CUBIC-WASPAS

CUBIC-WASPAS (Cubic-WASPAS — Cubic extension of WASPAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Jun, Y. B. Kim, C. S. Yang, K. O. in 2012. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.


Cuckoo Search

Guguk Kuşu Araması (Cuckoo Search)
CS algorithm
Cuckoo Search via Lévy Flights

Cuckoo Search (CS) is a population-based metaheuristic optimization algorithm introduced by Xin-She Yang and Suash Deb in 2009. It models the obligate brood-parasitism of cuckoo birds — which lay eggs in other birds' nests — combined with Lévy flight random walks that enable long-range exploration of the search space. The algorithm has proven effective in structural engineering design, machine learning hyperparameter tuning, and other continuous black-box optimization problems.

Population-based metaheuristic / swarm intelligence

Brood parasitism of cuckoo birds and Lévy flight random walks

Lévy flights for global exploration + abandon probability for exploitation

Yang, X.S. & Deb, S. (2009). Cuckoo Search via Lévy Flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 210-214. IEEE.

Yang, X.S. & Deb, S. (2013). Multiobjective Cuckoo Search for Design Optimization. Computers & Operations Research, 40(6), 1616-1624.

particle-swarm-optimization genetic-algorithm firefly-algorithm differential-evolution simulated-annealing harmony-search


CUDIT-R

Cannabis Use Disorder Identification Test—Revised

Adamson, Kay-Lambkin, Baker, Lewin, Thornton, Kelly, Sellman

The CUDIT-R is a brief, 8-item self-report screening instrument developed to identify cannabis use disorder and hazardous cannabis use patterns. Introduced by Adamson and colleagues in 2010 as a revision of the original CUDIT, the CUDIT-R improves brevity and screening efficiency while maintaining strong psychometric properties. It is designed for use in primary care, addiction treatment, and public health settings to detect problematic cannabis use and inform treatment allocation decisions.

Adamson, S. J., Kay-Lambkin, F. J., Baker, A. L., Lewin, T. J., Thornton, L., Kelly, B. J., & Sellman, J. D. (2010). An improved brief screening instrument for cannabis use disorder. Drug and Alcohol Dependence, 110(1–2), 55–60.

dudit sadq readiness-to-change-questionnaire brief-addiction-monitor


The Cultural Competence Assessment Instrument (CCA) is a 25-item self-report measure designed to assess healthcare providers' cultural competence across four key domains: diversity experience, awareness, sensitivity, and competence behaviors. Developed by Schim, Doorenbos, and Borse in 2003, the CCA evaluates nurses' and other clinicians' readiness to provide culturally responsive care to diverse patient populations.

Schim, S. M., Doorenbos, A. Z., & Borse, N. N. (2003). Cultural competence development in nursing education: An evolutionary process. Journal of Transcultural Nursing, 14(3), 236–244.


Cultural Humility Scale

The Cultural Humility Scale (CHS) is a self-report instrument designed to assess healthcare providers' capacity for cultural humility—a stance of openness, self-reflection, and power-sharing with patients from diverse cultural backgrounds. Originating from theoretical work by Tervalon and Murray-García (1998) and operationalized by Hook and colleagues (2013), the CHS measures clinicians' willingness to acknowledge limits in cultural knowledge, receptiveness to patient perspectives, and commitment to lifelong learning about culture. The instrument is widely used in medical, nursing, counseling, and other health professions education to evaluate trainees' readiness for culturally humble practice.

Tervalon, M., & Murray-García, J. (1998). Cultural humility versus cultural competence: A critical distinction in defining physician training outcomes in multicultural education. Journal of Health Care for the Poor and Underserved, 9(2), 117–125.

Hook, J. N., Davis, D. E., Owen, J., Worthington Jr., E. L., & Utsey, S. O. (2013). Cultural humility: Measuring openness to culturally diverse clients. Journal of Counseling Psychology, 60(3), 353–366.


Cultural Intelligence Scale

CQS
Cultural Intelligence
Cultural Quotient

The Cultural Intelligence Scale (CQS) is a 20-item measure assessing an individual's capability to function effectively in culturally diverse contexts and to adapt behavior appropriately across cultural settings. Developed by Christopher Earley and Soon Ang in the early 2000s, the CQS operationalizes cultural intelligence as a multidimensional competence involving cognitive, metacognitive, motivational, and behavioral components. The measure has become standard in organizational psychology and international business research for evaluating cross-cultural effectiveness.

Cultural competence and adaptability scale

Earley, P. C., & Ang, S. (2003). Cultural intelligence: Individual interactions across cultures. Stanford University Press.

Ang, S., Van Dyne, L., Koh, C., Ng, K. Y., Templer, K. J., Tay, C., & Chandrasekar, N. A. (2007). Cultural Intelligence: Its measurement and effects on cultural judgment and decision making, cultural adaptation and task performance. Management and Organization Review, 3(3), 335–371.

Rockstuhl, T., Seiler, S., Ang, S., Van Dyne, L., & Annen, H. (2011). Beyond general intelligence (IQ) and emotional intelligence (EQ): A meta-analysis of cultural intelligence research. Journal of International Business Studies, 42(3), 494–515.