WLenhard/cNORM: v3.2.0

Date: 2023.08.17 The release is a fundamental revision and extension of the cNORM package. Starting with version 3.2, cNORM is able to model psychometric data over age using beta binomial distributions. The beta-binomial distribution is a powerful approach for modeling psychometric test scores with a fixed maximum score and discrete outcomes. In psychometric testing, we often encounter situations where individuals answer a set number of questions or items, resulting in whole-number scores bounded by zero and the maximum possible score, as it is often the case in 1PL IRT modelling. The probability of answering each question correctly varies among individuals due to factors like ability or personal traits.

Changes:

• Parametric modelling with beta binomial functions now fully implemented
• S3 functions predict, plot and summary added for bet a binomial models
• Fixed input validation in getNormScoreSE
• Started intensive work on regularization in Taylor models (planned for v4.0)
• Vignette on modelling with beta binomial distribution
• Transition from lattice to ggplot2
• Code on covariates removed from the complete package
• cNORM-Demo vignette revised
• code simplification in plotting functions, parameters removed
• new parameter to plot raw scores in plotPercentiles (default FALSE)
• 'buildCnormObject' function added to help with compatibility (joins data and model to cnorm object)
• cNORM.GUI() updated
• datasets life, mortality and EPM removed
• performance optimization