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An Empirical Comparison Of The Effect Of Missing Data On Type I Error And Statistical Power Of The Likelihood Ratio Test For Differential Item Functioning: An Item Response Theory Approach Using The Graded Response Model, Patricia Rodriguez De Gil
An Empirical Comparison Of The Effect Of Missing Data On Type I Error And Statistical Power Of The Likelihood Ratio Test For Differential Item Functioning: An Item Response Theory Approach Using The Graded Response Model, Patricia Rodriguez De Gil
USF Tampa Graduate Theses and Dissertations
In the context of educational research, missing data arise when examinees omit or do not reach an item, which generates an item nonresponse problem. Using a simulation approach, in addition to conducting complete data analyses, this study compared the performance of six methods for treating item nonresponse in the context of differential item functioning (DIF). The effect of missing data on the Type I error and statistical power of the Likelihood Ratio test for DIF detection in small scales was examined in the context of Item Response Theory (IRT-LR), using polytomous, Likert-type data and the graded response model. The effect …