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A Monte Carlo study of the impact of missing data and differential item functioning on theta estimates from two polytomous Rasch family models.
J Appl Meas. 2007; 8(4):388-403.JA

Abstract

This paper examines the impact of differential item functioning (DIF), missing item values, and different methods for handling missing item values on theta estimates with data simulated from the partial credit model and Andrich's rating scale model. Both Rasch family models are commonly used when obtaining an estimate of a respondent's attitude. The degree of missing data, DIF magnitude, and the percentage of DIF items were varied in MCAR data conditions in which the focal group was 10% of the total population. Four methods for handling missing data were compared: complete-case analysis, mean substitution, hot-decking, and multiple imputation. Bias, RMSE, means, and standard errors of the theta estimates for the focal group were adversely affected by the amount and magnitude of DIF items. RMSE and fidelity coefficients for both the reference and focal group were adversely impacted by the amount of missing data. While all methods of handling missing data performed fairly similarly, multiple imputation and hot-decking showed slightly better performance.

Authors+Show Affiliations

Georgia State University, Department of Educational Policy Studies, Atlanta, GA 30302-3977, USA. cfurlow@gsu.eduNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

18250525

Citation

Furlow, Carolyn F., et al. "A Monte Carlo Study of the Impact of Missing Data and Differential Item Functioning On Theta Estimates From Two Polytomous Rasch Family Models." Journal of Applied Measurement, vol. 8, no. 4, 2007, pp. 388-403.
Furlow CF, Fouladi RT, Gagne P, et al. A Monte Carlo study of the impact of missing data and differential item functioning on theta estimates from two polytomous Rasch family models. J Appl Meas. 2007;8(4):388-403.
Furlow, C. F., Fouladi, R. T., Gagne, P., & Whittaker, T. A. (2007). A Monte Carlo study of the impact of missing data and differential item functioning on theta estimates from two polytomous Rasch family models. Journal of Applied Measurement, 8(4), 388-403.
Furlow CF, et al. A Monte Carlo Study of the Impact of Missing Data and Differential Item Functioning On Theta Estimates From Two Polytomous Rasch Family Models. J Appl Meas. 2007;8(4):388-403. PubMed PMID: 18250525.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A Monte Carlo study of the impact of missing data and differential item functioning on theta estimates from two polytomous Rasch family models. AU - Furlow,Carolyn F, AU - Fouladi,Rachel T, AU - Gagne,Phill, AU - Whittaker,Tiffany A, PY - 2008/2/6/pubmed PY - 2008/2/28/medline PY - 2008/2/6/entrez SP - 388 EP - 403 JF - Journal of applied measurement JO - J Appl Meas VL - 8 IS - 4 N2 - This paper examines the impact of differential item functioning (DIF), missing item values, and different methods for handling missing item values on theta estimates with data simulated from the partial credit model and Andrich's rating scale model. Both Rasch family models are commonly used when obtaining an estimate of a respondent's attitude. The degree of missing data, DIF magnitude, and the percentage of DIF items were varied in MCAR data conditions in which the focal group was 10% of the total population. Four methods for handling missing data were compared: complete-case analysis, mean substitution, hot-decking, and multiple imputation. Bias, RMSE, means, and standard errors of the theta estimates for the focal group were adversely affected by the amount and magnitude of DIF items. RMSE and fidelity coefficients for both the reference and focal group were adversely impacted by the amount of missing data. While all methods of handling missing data performed fairly similarly, multiple imputation and hot-decking showed slightly better performance. SN - 1529-7713 UR - https://www.unboundmedicine.com/medline/citation/18250525/A_Monte_Carlo_study_of_the_impact_of_missing_data_and_differential_item_functioning_on_theta_estimates_from_two_polytomous_Rasch_family_models_ DB - PRIME DP - Unbound Medicine ER -