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TestDataImputation (version 2.3)

Missing Item Responses Imputation for Test and Assessment Data

Description

Functions for imputing missing item responses for dichotomous and polytomous test and assessment data. This package enables missing imputation methods that are suitable for test and assessment data, including: listwise (LW) deletion (see De Ayala et al. 2001 ), treating as incorrect (IN, see Lord, 1974 ; Mislevy & Wu, 1996 ; Pohl et al., 2014 ), person mean imputation (PM), item mean imputation (IM), two-way (TW) and response function (RF) imputation, (see Sijtsma & van der Ark, 2003 ), logistic regression (LR) imputation, predictive mean matching (PMM), and expectation<80><93>maximization (EM) imputation (see Finch, 2008 ).

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Version

Install

install.packages('TestDataImputation')

Monthly Downloads

252

Version

2.3

License

GPL (>= 2)

Maintainer

Shenghai Dai

Last Published

October 18th, 2021

Functions in TestDataImputation (2.3)

TreatIncorrect

Treat missing responses as incorrect (IN)
ImputeTestData

This main function imputes for missing responses using selected method
ItemMean

Item Mean (IM) Imputation
EMimpute

EM Imputation
ResponseFun

Response Function Imputation (RF)
micePMM

Predictive mean matching (PMM)
Twoway

Two-Way Imputation (TW)
Listwise

Listwise Deletion (LW)
LogisticReg

Logistic Regression (LR) Imputation
test.data

Example test data
PersonMean

Person Mean Imputation (PM)