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題名 Bayesian inference with spike-and-slab priors for differential item functioning detection in a multiple-group IRT tree model
作者 張育瑋
Chang, Yu-Wei;Yang, Cheng-Xin
貢獻者 統計系
關鍵詞 Bayesian estimation; differential item functioning; item response theory tree model; missing data; spike-and-slab priors
日期 2024-05
上傳時間 26-Mar-2024 15:24:05 (UTC+8)
摘要 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.
關聯 Journal of Statistical Computation and Simulation, Vol.94, No.7, pp.1416-1444
資料類型 article
DOI https://doi.org/10.1080/00949655.2023.2289056
dc.contributor 統計系-
dc.creator (作者) 張育瑋-
dc.creator (作者) Chang, Yu-Wei;Yang, Cheng-Xin-
dc.date (日期) 2024-05-
dc.date.accessioned 26-Mar-2024 15:24:05 (UTC+8)-
dc.date.available 26-Mar-2024 15:24:05 (UTC+8)-
dc.date.issued (上傳時間) 26-Mar-2024 15:24:05 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/150567-
dc.description.abstract (摘要) 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.-
dc.format.extent 109 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Journal of Statistical Computation and Simulation, Vol.94, No.7, pp.1416-1444-
dc.subject (關鍵詞) Bayesian estimation; differential item functioning; item response theory tree model; missing data; spike-and-slab priors-
dc.title (題名) Bayesian inference with spike-and-slab priors for differential item functioning detection in a multiple-group IRT tree model-
dc.type (資料類型) article-
dc.identifier.doi (DOI) 10.1080/00949655.2023.2289056-
dc.doi.uri (DOI) https://doi.org/10.1080/00949655.2023.2289056-