Effects on the Linear Logistic Test Model’s Cognitive Components When the Person Distribution Is Skewed

• In Event: Poster Session 9
  In Poster Session: Applications of Cognitive Diagnostic Models: From Q-Matrix Development to Data-Model Fit

Abstract

A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included overall type of misspecification (under-, balanced-, and over-specification), percent misspecified (1%, 5%, 10%, and 15%), sample size (20, 40, 80, 160, 320, 640, and 1280), Q-matrix density (64% and 46%), skewness of ability distribution (-0.5, 0, and 0.5), and test length (20, 40, and 60 items). Statistical bias, RMSE, CI coverage, and CI width were computed. Results were interpreted for the design factors and recommendations for the application of LLTM provided.

Authors

• George T. MacDonald, University of South Florida

• Yi-Hsin Chen, University of South Florida