Evaluating the Performances of Missing Data Handling Methods in Ability Estimation From Sparse Data.

Large amounts of missing data could distort item parameter estimation and lead to biased ability estimates in educational assessments. Therefore, missing responses should be handled properly before estimating any parameters. In this study, two Monte Carlo simulation studies were conducted to compare...

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Detalles Bibliográficos

Publicado en:	Educational & Psychological Measurement Vol. 80; no. 5; pp. 932 - 955
Autores principales:	Xiao, Jiaying, Bulut, Okan
Formato:	Artículo
Publicado:	Sage Publications Inc. Oct2020
Materias:	Computer simulation Database management Database evaluation Statistical sampling Statistics Data analysis Research bias Random forest algorithms
Acceso en línea:	Ver este registro en EBSCOhost