Sample Size Requirements for Applying Diagnostic Classification Models.

Front Psychol

Educational Psychology Department, College of Education, University of Georgia, Athens, GA, United States.

Published: January 2021

Results of a comprehensive simulation study are reported investigating the effects of sample size, test length, number of attributes and base rate of mastery on item parameter recovery and classification accuracy of four DCMs (i.e., C-RUM, DINA, DINO, and LCDMREDUCED). Effects were evaluated using bias and RMSE computed between true (i.e., generating) parameters and estimated parameters. Effects of simulated factors on attribute assignment were also evaluated using the percentage of classification accuracy. More precise estimates of item parameters were obtained with larger sample size and longer test length. Recovery of item parameters decreased as the number of attributes increased from three to five but base rate of mastery had a varying effect on the item recovery. Item parameter and classification accuracy were higher for DINA and DINO models.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7868330PMC
http://dx.doi.org/10.3389/fpsyg.2020.621251DOI Listing

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