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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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Fox, J.-P.; Wyrick, Cheryl – Journal of Educational and Behavioral Statistics, 2008
The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called randomized item responses are observed. A relationship is specified between randomized item response data and true item response data. True item response data are modeled with a (non)linear…
Descriptors: Item Response Theory, Models, Markov Processes, Monte Carlo Methods
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Gelman, Andrew – Journal of Educational and Behavioral Statistics, 1997
Several classroom demonstrations are described that have sparked student involvement in undergraduate courses in probability and statistics. These demonstrations involve experimentation using exams and statistical analysis and adjustment of exam scores. (Author/SLD)
Descriptors: Classroom Techniques, College Faculty, College Students, Higher Education
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Fox, Jean-Paul – Journal of Educational and Behavioral Statistics, 2005
The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…
Descriptors: Item Response Theory, Models, Probability, Markov Processes