TY - JOUR
T1 - Multidimensional Item Response Theory Models with Collateral Information as Poisson Regression Models
AU - Anderson, Carolyn J.
PY - 2013/7
Y1 - 2013/7
N2 - Multiple choice items on tests and Likert items on surveys are ubiquitous in educational, social and behavioral science research; however, methods for analyzing of such data can be problematic. Multidimensional item response theory models are proposed that yield structured Poisson regression models for the joint distribution of responses to items. The methodology presented here extends the approach described in Anderson, Verkuilen, and Peyton (2010) that used fully conditionally specified multinomial logistic regression models as item response functions. In this paper, covariates are added as predictors of the latent variables along with covariates as predictors of location parameters. Furthermore, the models presented here incorporate ordinal information of the response options thus allowing an empirical examination of assumptions regarding the ordering and the estimation of optimal scoring of the response options. To illustrate the methodology and flexibility of the models, data from a study on aggression in middle school (Espelage, Holt, and Henkel 2004) is analyzed. The models are fit to data using SAS.
AB - Multiple choice items on tests and Likert items on surveys are ubiquitous in educational, social and behavioral science research; however, methods for analyzing of such data can be problematic. Multidimensional item response theory models are proposed that yield structured Poisson regression models for the joint distribution of responses to items. The methodology presented here extends the approach described in Anderson, Verkuilen, and Peyton (2010) that used fully conditionally specified multinomial logistic regression models as item response functions. In this paper, covariates are added as predictors of the latent variables along with covariates as predictors of location parameters. Furthermore, the models presented here incorporate ordinal information of the response options thus allowing an empirical examination of assumptions regarding the ordering and the estimation of optimal scoring of the response options. To illustrate the methodology and flexibility of the models, data from a study on aggression in middle school (Espelage, Holt, and Henkel 2004) is analyzed. The models are fit to data using SAS.
KW - Constrained optimization
KW - Covariates
KW - Fully conditionally specified models
KW - Log-multiplicative association models
KW - Ordinal response scales
KW - Polytomous items
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U2 - 10.1007/s00357-013-9131-x
DO - 10.1007/s00357-013-9131-x
M3 - Article
AN - SCOPUS:84880339352
SN - 0176-4268
VL - 30
SP - 276
EP - 303
JO - Journal of Classification
JF - Journal of Classification
IS - 2
ER -