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John Mart V. DelosReyes; Miguel A. Padilla – Journal of Experimental Education, 2024
Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…
Descriptors: Research Problems, Correlation, Intervals, Computation
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Waterbury, Glenn Thomas; DeMars, Christine E. – Journal of Experimental Education, 2019
There is a need for effect sizes that are readily interpretable by a broad audience. One index that might fill this need is [pi], which represents the proportion of scores in one group that exceed the mean of another group. The robustness of estimates of [pi] to violations of normality had not been explored. Using simulated data, three estimates…
Descriptors: Effect Size, Robustness (Statistics), Simulation, Research Methodology
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Li, Jian; Lomax, Richard G. – Journal of Experimental Education, 2017
Using Monte Carlo simulations, this research examined the performance of four missing data methods in SEM under different multivariate distributional conditions. The effects of four independent variables (sample size, missing proportion, distribution shape, and factor loading magnitude) were investigated on six outcome variables: convergence rate,…
Descriptors: Monte Carlo Methods, Structural Equation Models, Evaluation Methods, Measurement Techniques
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Sun, Shuyan; Pan, Wei – Journal of Experimental Education, 2013
Regression discontinuity design is an alternative to randomized experiments to make causal inference when random assignment is not possible. This article first presents the formal identification and estimation of regression discontinuity treatment effects in the framework of Rubin's causal model, followed by a thorough literature review of…
Descriptors: Regression (Statistics), Computation, Accuracy, Causal Models