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iarm (version 0.4.3)

Item Analysis in Rasch Models

Description

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).

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Version

Install

install.packages('iarm')

Monthly Downloads

251

Version

0.4.3

License

GPL-2

Maintainer

Marianne Mueller

Last Published

August 27th, 2022

Functions in iarm (0.4.3)

test_prop

Properties of the Test
boot_fit

Computes Bootstrapping P Values for Outfit and Infit Statistics
amts

Abbreviated Mental Test Score (AMTS)
print.bootfit

Print Method for the Output of boot_fit
partgam_DIF

Partial Gamma to detect Differential Item Functioning (DIF)
score_groups

Generate two Score Groups
print.outfit

Print Method for the Output of out_infit
partgam_LD

Partial Gamma to detect Local Dependence (LD)
person_estimates

Person Estimates with MLE and WLE
item_restscore

Item Restscore Association
item_target

Computation of Item Targets for Polytomous Models
ICCplot

Item Characteristic Curves
clr_tests

Conditional Likelihood Ratio Tests (CLR)
iarm-package

iarm: A package for item analysis in Rasch models
item_obsexp

Observed and Expected Item Mean Scores
out_infit

Item Outfit and Infit Statistics
desc2

Depression Screening DESC-II
partgam

Conditional and Partial Gamma Coefficients