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Tal, Yael; Kukliansky, Ida – Journal of Statistics Education, 2020
The aim of this study is to explore the judgments and reasoning in probabilistic tasks that require comparing two probabilities either with or without introducing an additional degree of uncertainty. The reasoning associated with the task having an additional condition of uncertainty has not been discussed in previous studies. The 66 undergraduate…
Descriptors: Undergraduate Students, Comparative Analysis, Statistics, Probability
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Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane – Journal of Educational and Behavioral Statistics, 2015
Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…
Descriptors: Structural Equation Models, Nonparametric Statistics, Regression (Statistics), Maximum Likelihood Statistics
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Koran, Jennifer – Measurement and Evaluation in Counseling and Development, 2016
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.
Descriptors: Factor Analysis, Sample Size, Models, Sampling
Welge-Crow, Patricia A.; And Others – 1990
Three strategies for augmenting the interpretation of significance test results are illustrated. Determining the most suitable indices to use in evaluating empirical results is a matter of considerable debate among researchers. Researchers increasingly recognize that significance tests are very limited in their potential to inform the…
Descriptors: Educational Research, Effect Size, Estimation (Mathematics), Generalizability Theory
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DeSarbo, Wayne S.; And Others – Psychometrika, 1996
A stochastic multidimensional unfolding (MDU) procedure is presented to represent individual differences in phased or sequential decision processes spatially. A Monte Carlo analysis demonstrates estimation proficiency and the appropriateness of the proposed model selection heuristic, and an application to capture awareness, consideration, and…
Descriptors: Cognitive Processes, Consumer Economics, Decision Making, Estimation (Mathematics)