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.

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