Monte Carlo Simulation in Item Response Theory Applications Using SAS

被引:2
|
作者
Ames, Allison J. [1 ]
Leventhal, Brian C. [2 ]
Ezike, Nnamdi C. [1 ]
机构
[1] Univ Arkansas, Educ Stat & Res Methods, 238 Grad Educ Bldg,751 W Maple St, Fayetteville, AR 72701 USA
[2] James Madison Univ, Grad Psychol, Harrisonburg, VA 22807 USA
关键词
Item response theory; simulation techniques; statistical software; MAXIMUM-LIKELIHOOD-ESTIMATION; FIT INDEX; IRT; PERFORMANCE; S-X-2;
D O I
10.1080/15366367.2019.1689762
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
Data simulation and Monte Carlo simulation studies are important skills for researchers and practitioners of educational and psychological measurement, but there are few resources on the topic specific to item response theory. Even fewer resources exist on the statistical software techniques to implement simulation studies. This article presents an introduction to the questions that simulation studies can, and cannot answer, along with the primary steps of the simulation study. We primarily focus on the parts of the simulation for which statistical software is used, presenting syntax for simulating 2PL data, and discuss how to extend the basic syntax to more complex models. We focus on SAS software in the article to build upon an existing syntax base, as most universities have SAS licenses. Two small simulations serve as didactic illustrations and to demonstrate parameter recovery of the SAS IRT procedure and an evaluation of the procedure's item-fit options.
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页码:55 / 74
页数:20
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