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題名 Modeling Guessing Components in the Measurement of Political Knowledge
作者 蔡宗漢
Tsai, Tsung-han;Lin, Chang-chih
貢獻者 政治系
日期 2017-10
上傳時間 14-Nov-2017 16:38:38 (UTC+8)
摘要 Due to the crucial role of political knowledge in democratic participation, the measurement of political knowledge has been a major concern in the discipline of political science. Common formats used for political knowledge questions include multiple-choice items and open-ended identification questions. The conventional wisdom holds that multiple-choice items induce guessing behavior, which leads to underestimated item-difficulty parameters and biased estimates of political knowledge. This article examines guessing behavior in multiple-choice items and argues that a successful guess requires certain levels of knowledge conditional on the difficulties of items. To deal with this issue, we propose a Bayesian IRT guessing model that accommodates the guessing components of item responses. The proposed model is applied to analyzing survey data in Taiwan, and the results show that the proposed model appropriately describes the guessing components based on respondents’ levels of political knowledge and item characteristics. That is, in general, partially informed respondents are more likely to have a successful guess because well-informed respondents do not need to guess and barely informed ones are highly seducible by the attractive distractors. We also examine the gender gap in political knowledge and find that, even when the guessing effect is accounted for, men are more knowledgeable than women about political affairs, which is consistent with the literature.
關聯 Political Analysis, Vol.25, No.4, pp.483-504
資料類型 article
DOI https://doi.org/10.1017/pan.2017.21
dc.contributor 政治系
dc.creator (作者) 蔡宗漢zh_TW
dc.creator (作者) Tsai, Tsung-han;Lin, Chang-chihen_US
dc.date (日期) 2017-10
dc.date.accessioned 14-Nov-2017 16:38:38 (UTC+8)-
dc.date.available 14-Nov-2017 16:38:38 (UTC+8)-
dc.date.issued (上傳時間) 14-Nov-2017 16:38:38 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/114659-
dc.description.abstract (摘要) Due to the crucial role of political knowledge in democratic participation, the measurement of political knowledge has been a major concern in the discipline of political science. Common formats used for political knowledge questions include multiple-choice items and open-ended identification questions. The conventional wisdom holds that multiple-choice items induce guessing behavior, which leads to underestimated item-difficulty parameters and biased estimates of political knowledge. This article examines guessing behavior in multiple-choice items and argues that a successful guess requires certain levels of knowledge conditional on the difficulties of items. To deal with this issue, we propose a Bayesian IRT guessing model that accommodates the guessing components of item responses. The proposed model is applied to analyzing survey data in Taiwan, and the results show that the proposed model appropriately describes the guessing components based on respondents’ levels of political knowledge and item characteristics. That is, in general, partially informed respondents are more likely to have a successful guess because well-informed respondents do not need to guess and barely informed ones are highly seducible by the attractive distractors. We also examine the gender gap in political knowledge and find that, even when the guessing effect is accounted for, men are more knowledgeable than women about political affairs, which is consistent with the literature.en_US
dc.format.extent 819338 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Political Analysis, Vol.25, No.4, pp.483-504
dc.title (題名) Modeling Guessing Components in the Measurement of Political Knowledgezh_TW
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1017/pan.2017.21
dc.doi.uri (DOI) https://doi.org/10.1017/pan.2017.21