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Direct linkKaplan, David; Chen, Jianshen; Lyu, Weicong; Yavuz, Sinan – Grantee Submission, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
Download full textKaplan, David; Chen, Jianschen; Yavuz, Sinan; Lyu, Weicong – Grantee Submission, 2022
The purpose of this paper is to demonstrate and evaluate the use of "Bayesian dynamic borrowing"(Viele et al, in Pharm Stat 13:41-54, 2014) as a means of systematically utilizing historical information with specific applications to large-scale educational assessments. Dynamic borrowing via Bayesian hierarchical models is a special case…
Descriptors: Bayesian Statistics, Models, Prediction, Accuracy
Kaplan, David; Chen, Jianshen; Lyu, Weicong; Yavuz, Sinan – Large-scale Assessments in Education, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
