Item Parameter Estimation in Multistage Designs: A Comparison of Different Estimation Approaches for the Rasch Model by Jan Steinfeld, Alexander Robitzsch

“…Zwitser and Maris (2015, <i>Psychometrika</i>) proposed a modified conditional maximum likelihood estimation method for multistage designs that provides practically unbiased item parameter estimates. …”
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Bayesian historical borrowing with longitudinal large-scale assessments by David Kaplan, Jianshen Chen, Weicong Lyu, Sinan Yavuz

“…Overall, Bayesian dynamic borrowing and commensurate priors are no worse, and in some cases better, than other methods in terms of parameter recovery and predictive performance, and considering a previous paper by Kaplan et al. (Psychometrika, 10.1007/s11336-022-09869-3, 2022) found clear benefits of Bayesian dynamic borrowing over other methods of historical borrowing in the multilevel context using data from the Program for International Student Assessment (PISA) with five historical cycles, this paper argues that Bayesian dynamic borrowing or commensurate priors is a prudent choice for borrowing information from previous cycles of longitudinal data.…”
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