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Smithson, Michael; Merkle, Edgar C.; Verkuilen, Jay – Journal of Educational and Behavioral Statistics, 2011
This paper describes the application of finite-mixture general linear models based on the beta distribution to modeling response styles, polarization, anchoring, and priming effects in probability judgments. These models, in turn, enhance our capacity for explicitly testing models and theories regarding the aforementioned phenomena. The mixture…
Descriptors: Priming, Research Methodology, Probability, Item Response Theory
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Camparo, James; Camparo, Lorinda B. – Journal of Educational and Behavioral Statistics, 2013
Though ubiquitous, Likert scaling's traditional mode of analysis is often unable to uncover all of the valid information in a data set. Here, the authors discuss a solution to this problem based on methodology developed by quantum physicists: the state multipole method. The authors demonstrate the relative ease and value of this method by…
Descriptors: Ethnic Groups, Social Science Research, Evaluation Methods, Behavioral Science Research
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Cohen, Michael P. – Journal of Educational and Behavioral Statistics, 2000
Compares the odds ratio with the probability ratio (relative risk). These quantities arise, for example, in the analysis of educational and social science through logistic regression. (Author/SLD)
Descriptors: Educational Research, Probability, Regression (Statistics), Research Methodology
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Pan, Wei; Frank, Kenneth A. – Journal of Educational and Behavioral Statistics, 2003
Causal inference is an important, controversial topic in the social sciences, where it is difficult to conduct experiments or measure and control for all confounding variables. To address this concern, the present study presents a probability index to assess the robustness of a causal inference to the impact of a confounding variable. The…
Descriptors: Research Methodology, Educational Attainment, Social Sciences, Program Effectiveness