Item Analysis in Rasch Models
Computes Bootstrapping P Values for Outfit and Infit Statistics
Conditional Likelihood Ratio Tests (CLR)
iarm: A package for item analysis in Rasch models
Item Characteristic Curves
Observed and Expected Item Mean Scores
Item Restscore Association
Computation of Item Targets for Polytomous Models
Item Outfit and Infit Statistics
Conditional and Partial Gamma Coefficients
Partial Gamma to detect Differential Item Functioning (DIF)
Partial Gamma to detect Local Dependence (LD)
Person Estimates with MLE and WLE
Print Method for the Output of boot_fit
Print Method for the Output of out_infit
Generate two Score Groups
Properties of the Test
Tools to assess model fit and identify misfitting items for Rasch models (RM) and partial credit models (PCM). Included are item fit statistics, item characteristic curves, item-restscore association, conditional likelihood ratio tests, assessment of measurement error, estimates of the reliability and test targeting as described in Christensen et al. (Eds.) (2013, ISBN:978-1-84821-222-0).