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Published October 4, 2021 | Version v0.5.0
Software Open

easystats/effectsize: CRAN release 0.5.0

  • 1. Ben-Gurion University of the Negev
  • 2. Nanyang Technological University
  • 3. Universitätsklinikum Hamburg-Eppendorf
  • 4. esqLABS
  • 5. @actions
  • 6. UIUC

Description

effectsize 0.5 Breaking Changes
  • cramers_v() correctly does not work with 1-dimentional tables (for goodness-of-fit tests).
  • interpret_d(), interpret_g(), and interpret_delta() are now interpret_cohens_d(), interpret_hedges_g(), and interpret_glass_delta().
  • interpret_parameters() was removed. Use interpret_r() instead (with caution!).
  • Phi, Cohen's w, Cramer's V, ANOVA effect sizes, rank Epsilon squared, Kendall's W - CIs default to 95% one-sided CIs (alternative = "greater"). (To restore previous behavior, set ci = .9, alternative = "two.sided".)
  • adjust(), change_scale(), normalize(), ranktransform(), standardize() (data), and unstandardize() have moved to the new {datawizard} package!
New features
  • pearsons_c() (and chisq_to_pearsons_c()) for estimating Pearson's contingency coefficient.
  • interpret_vif() for interpretation of variance inflation factors.
  • oddsratio_to_riskratio() can now convert OR coefficients to RR coefficients from a logistic GLM(M).
  • All effect-size functions gain an alternative argument which can be used to make one- or two-sided CIs.
  • interpret() now accepts as input the results from cohens_d(), eta_squared(), rank_biserial(), etc.
  • interpret_pd() for the interpretation of the Probability of Direction.
Bug fixes
  • kendalls_w() CIs now correctly bootstrap samples from the raw data (previously the rank-transformed data was sampled from).
  • cohens_d(), sd_pooled() and rank_biserial() now properly respect when y is a grouping character vector.
  • effectsize() for Chi-squared test of goodness-of-fit now correctly respects non-uniform expected probabilities ( #352 ).
Changes
  • interpret_bf() now accepts log(BF) as input.

Files

easystats/effectsize-v0.5.0.zip

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