Literature DB >> 22545594

Modeling multiple response processes in judgment and choice.

Ulf Böckenholt1.   

Abstract

In this article, I show how item response models can be used to capture multiple response processes in psychological applications. Intuitive and analytical responses, agree-disagree answers, response refusals, socially desirable responding, differential item functioning, and choices among multiple options are considered. In each of these cases, I show that the response processes can be measured via pseudoitems derived from the observed responses. The estimation of these models via standard software programs that allow for missing data is also discussed. The article concludes with two detailed applications that illustrate the prevalence of multiple response processes. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Mesh:

Year:  2012        PMID: 22545594     DOI: 10.1037/a0028111

Source DB:  PubMed          Journal:  Psychol Methods        ISSN: 1082-989X


  22 in total

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Authors:  Minjeong Park; Amery D Wu
Journal:  Educ Psychol Meas       Date:  2019-02-15       Impact factor: 2.821

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7.  Modeling Intensive Polytomous Time-Series Eye-Tracking Data: A Dynamic Tree-Based Item Response Model.

Authors:  Sun-Joo Cho; Sarah Brown-Schmidt; Paul De Boeck; Jianhong Shen
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8.  Extreme Response Style and the Measurement of Intra-Individual Variability in Affect.

Authors:  Sien Deng; Danielle E McCarthy; Megan E Piper; Timothy B Baker; Daniel M Bolt
Journal:  Multivariate Behav Res       Date:  2018-01-11       Impact factor: 5.923

9.  Analysis of Multiple Partially Ordered Responses to Belief Items with Don't Know Option.

Authors:  Edward H Ip; Shyh-Huei Chen; Sara A Quandt
Journal:  Psychometrika       Date:  2014-12-06       Impact factor: 2.500

10.  Using multidimensional item response theory to evaluate how response styles impact measurement.

Authors:  Daniel J Adams; Daniel M Bolt; Sien Deng; Stevens S Smith; Timothy B Baker
Journal:  Br J Math Stat Psychol       Date:  2019-03-28       Impact factor: 3.380

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