Bayesian Latent Growth Curve Model with Application to Item Response Data
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Authors
Liu, Bo
Issue Date
2021
Type
Thesis
Language
Keywords
Bayesian analysis , Gibbs sampling , Growth curve model , Item response theory , Longitudinal data analysis , Markov chain Monte Carlo
Alternative Title
Abstract
The discovery of the effectiveness of students' learning and instructors' teaching is a challenge in educational assessment. To study educational progress, we propose a flexible latent variable model to model individual differences in growth given longitudinal item response data. We developed a Bayesian growth curve model together with an MCMC algorithm to estimate the student ability and quantify the influence of test items and target covariates. A simulation study and analysis of real data are conducted to demonstrate the performance of the proposed method.
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Citation
Publisher
License
Creative Commons Attribution 4.0 United States