A Comparison of Latent Class Analysis and the Mixture Rasch Model Using 8th Grade Mathematics Data in the Fourth International Mathematics and Science Study (TIMSS-2011)

Authors : Turker TOKER, Kathy GREEN

Pages : 959-974

Doi:10.21449/ijate.1024251

View : 26 | Download : 10

Publication Date : 2021-12-04

Article Type : Research Paper

Abstract :This study provides a comparison of the results of latent class analysis insert ignore into journalissuearticles values(LCA); and mixture Rasch model insert ignore into journalissuearticles values(MRM); analysis using data from the Trends in International Mathematics and Science Study – 2011 insert ignore into journalissuearticles values(TIMSS-2011); with a focus on the 8th-grade mathematics section. The research study focuses on the comparison of LCA and MRM to determine if results obtained differ when the assumed psychometric model differs. Also, a log-linear analysis was conducted to understand the interactions between latent classes identified by LCA and MRM. Response data to the three booklets were used to run latent class analysis using Mplus 7.31 insert ignore into journalissuearticles values(Muthén & Muthén, 2012a); for LCA and WINMIRA insert ignore into journalissuearticles values(von Davier, 2001a);. The findings of this paper do not reveal unequivocally whether a model based on primarily qualitative differences insert ignore into journalissuearticles values(LCA);, that is, different strategies, instructional differences, curriculum etc. or a model including additional factors of quantitative differences within strategies insert ignore into journalissuearticles values(MRM); should be used with this particular dataset. Both of the tests provided similar results with more or less similar interpretations. Both techniques fit the data similarly, a result found in prior research. Nonetheless, for tests similar to TIMSS exams, item difficulty parameters can be useful for educational researchers giving potential priority to use of MRM.
Keywords : Latent class analysis, The Mixture Rasch model, Psychometrics, Mathematics, Validation