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題名 An Item Response Tree Model with Not-All-Distinct End Nodes for Non-Response Modeling 作者 張育瑋
Chang, Yu-Wei
Hsu, Nan-Jung
Tsai, Rung-Ching貢獻者 統計系 關鍵詞 Laplace-approximated maximum likelihood estimation;item response theory tree model;non-response 日期 2021-11 上傳時間 2022-04-12 摘要 The non-response model in Knott et al. (1991, Statistician, 40, 217) can be represented as a tree model with one branch for response/non-response and another branch for correct/incorrect response, and each branch probability is characterized by an item response theory model. In the model, it is assumed that there is only one source of non-responses. However, in questionnaires or educational tests, non-responses might come from different sources, such as test speededness, inability to answer, lack of motivation, and sensitive questions. To better accommodate such more realistic underlying mechanisms, we propose a a tree model with four end nodes, not all distinct, for non-response modelling. The Laplace-approximated maximum likelihood estimation for the proposed model is suggested. The validation of the proposed estimation procedure and the advantage of the proposed model over traditional methods are demonstrated in simulations. For illustration, the methodologies are applied to data from the 2012 Programme for International Student Assessment (PISA). The analysis shows that the proposed tree model has a better fit to PISA data than other existing models, providing a useful tool to distinguish the sources of non-responses. 關聯 British Journal of Mathematical and Statistical Psychology, Vol.74, No.3, pp.487-512 資料類型 article DOI https://doi.org/10.1111/bmsp.12236 dc.contributor 統計系 dc.creator (作者) 張育瑋 dc.creator (作者) Chang, Yu-Wei dc.creator (作者) Hsu, Nan-Jung dc.creator (作者) Tsai, Rung-Ching dc.date (日期) 2021-11 dc.date.accessioned 2022-04-12 - dc.date.available 2022-04-12 - dc.date.issued (上傳時間) 2022-04-12 - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/139851 - dc.description.abstract (摘要) The non-response model in Knott et al. (1991, Statistician, 40, 217) can be represented as a tree model with one branch for response/non-response and another branch for correct/incorrect response, and each branch probability is characterized by an item response theory model. In the model, it is assumed that there is only one source of non-responses. However, in questionnaires or educational tests, non-responses might come from different sources, such as test speededness, inability to answer, lack of motivation, and sensitive questions. To better accommodate such more realistic underlying mechanisms, we propose a a tree model with four end nodes, not all distinct, for non-response modelling. The Laplace-approximated maximum likelihood estimation for the proposed model is suggested. The validation of the proposed estimation procedure and the advantage of the proposed model over traditional methods are demonstrated in simulations. For illustration, the methodologies are applied to data from the 2012 Programme for International Student Assessment (PISA). The analysis shows that the proposed tree model has a better fit to PISA data than other existing models, providing a useful tool to distinguish the sources of non-responses. dc.format.extent 701693 bytes - dc.format.mimetype application/pdf - dc.relation (關聯) British Journal of Mathematical and Statistical Psychology, Vol.74, No.3, pp.487-512 dc.subject (關鍵詞) Laplace-approximated maximum likelihood estimation;item response theory tree model;non-response dc.title (題名) An Item Response Tree Model with Not-All-Distinct End Nodes for Non-Response Modeling dc.type (資料類型) article dc.identifier.doi (DOI) 10.1111/bmsp.12236 dc.doi.uri (DOI) https://doi.org/10.1111/bmsp.12236
