Additive Multilevel Item Structure Models with Random Residuals: Item Modeling for Explanation and Item Generation

作者：Cho Sun Joo^*; De Boeck Paul; Embretson Susan; Rabe Hesketh Sophia

来源：Psychometrika, 2014, 79(1): 84-104.

DOI：10.1007/s11336-013-9360-2

• alternating imputation posterior with adaptive quadrature
• item generation
• multilevel model
• random item parameters

An additive multilevel item structure (AMIS) model with random residuals is proposed. The model includes multilevel latent regressions of item discrimination and item difficulty parameters on covariates at both item and item category levels with random residuals at both levels. The AMIS model is useful for explanation purposes and also for prediction purposes as in an item generation context. The parameters can be estimated with an alternating imputation posterior algorithm that makes use of adaptive quadrature, and the performance of this algorithm is evaluated in a simulation study.

• 出版日期2014-1