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Schoeneberger, Jason A. – Journal of Experimental Education, 2016
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Descriptors: Sample Size, Models, Computation, Predictor Variables
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Lai, Mark H. C.; Kwok, Oi-man – Journal of Experimental Education, 2015
Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…
Descriptors: Educational Research, Research Design, Cluster Grouping, Statistical Data
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Kennedy, Eugene – Journal of Experimental Education, 1988
Ridge estimates (REs) of population beta weights were compared to ordinary least squares (OLS) estimates through computer simulation to evaluate the use of REs in explanatory research. With fixed predictors, there was some question of the consistency of ridge regression, but with random predictors, REs were superior to OLS. (SLD)
Descriptors: Computer Simulation, Error of Measurement, Estimation (Mathematics), Least Squares Statistics