Multilevel Item Response Model with Heterogeneous Within-Cluster Variances

被引:0
|
作者
Kara, Yusuf [1 ]
Kamata, Akihito [1 ]
机构
[1] Southern Methodist Univ, Ctr Res & Evaluat, Dallas, TX USA
来源
JOURNAL OF EXPERIMENTAL EDUCATION | 2022年 / 90卷 / 04期
关键词
Bayesian estimation; multilevel IRT; multilevel model; school effectiveness; variance heterogeneity; LOCATION SCALE-MODEL; IRT; ROBUSTNESS; FRAMEWORK; DISTRIBUTIONS; COMPONENTS; GROWTH; BAYES; MCMC;
D O I
10.1080/00220973.2020.1858015
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Within-cluster variance homogeneity is one of the key assumptions of multilevel models; however, assuming a constant (i.e. equal) within-cluster variance may not be realistic. Moreover, existent within-cluster variance heterogeneity should be regarded as a source of additional information rather than a violation of a model assumption. This study extends the three-level Rasch item response model to estimate cluster-specific variances as random effects adopting the Bayesian approach. Data analysis results provided empirical evidence for the possible violations of the within-cluster variance heterogeneity, as well as the utility of the proposed heterogeneous model. A small-scale simulation study conducted to provide information about the estimation efficiency of the model parameters with varying degrees of within-cluster variance heterogeneity.
引用
收藏
页码:962 / 980
页数:19
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