Please use this identifier to cite or link to this item:

Title: Modeling Guessing Components in the Measurement of Political Knowledge
Authors: 蔡宗漢
Tsai, Tsung-han;Lin, Chang-chih
Contributors: 政治系
Date: 2017-10
Issue Date: 2017-11-14 16:38:38 (UTC+8)
Abstract: 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.
Relation: Political Analysis, Vol.25, No.4, pp.483-504
Data Type: article
DOI 連結:
Appears in Collections:[國家發展研究所] 期刊論文

Files in This Item:

File SizeFormat
483504.pdf800KbAdobe PDF352View/Open

All items in 學術集成 are protected by copyright, with all rights reserved.

社群 sharing