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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/150567

Title:	Bayesian inference with spike-and-slab priors for differential item functioning detection in a multiple-group IRT tree model
Authors:	張育瑋 Chang, Yu-Wei;Yang, Cheng-Xin
Contributors:	統計系
Keywords:	Bayesian estimation;differential item functioning;item response theory tree model;missing data;spike-and-slab priors
Date:	2023-12
Issue Date:	2024-03-26 15:24:05 (UTC+8)
Abstract:	Group differences have practical implications in analysing data from achievement tests or questionnaires. In the current study, we develop a model that accounts for between-group differences, differential item functioning (DIF), latent factors, and missing item response data simultaneously. Different from most of the present DIF studies where one has to iteratively select anchor items and detect DIF items, we achieve DIF detection and parameter estimation simultaneously by properly reparameterizing model parameters and applying some spike-and-slab priors (Ishwaran & Rao, Spike and slab variable selection: frequentist and Bayesian strategies. Ann Stat. 2005a;33:730–773; Ročková & George, The spike-and-slab LASSO. J Am Stat Assoc. 2018;113:431–444) in Bayesian estimation. Simulation studies are conducted to illustrate the validation of the proposed estimation procedure and the efficiency of DIF detection. The proposed method is further applied to a real dataset for illustration.
Relation:	Journal of Statistical Computation and Simulation
Data Type:	article
DOI 連結:	https://doi.org/10.1080/00949655.2023.2289056
DOI:	10.1080/00949655.2023.2289056
Appears in Collections:	[統計學系] 期刊論文

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