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Peng, Peng; Namkung, Jessica; Barnes, Marcia; Sun, Congying – Journal of Educational Psychology, 2016
The purpose of this meta-analysis was to determine the relation between mathematics and working memory (WM) and to identify possible moderators of this relation including domains of WM, types of mathematics skills, and sample type. A meta-analysis of 110 studies with 829 effect sizes found a significant medium correlation of mathematics and WM, r…
Descriptors: Meta Analysis, Mathematics, Short Term Memory, Mathematics Skills
Valliant, Richard; Dever, Jill A.; Kreuter, Frauke – Springer, 2013
Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least…
Descriptors: Sampling, Surveys, Computer Software, College Students
Luh, Wei-Ming; Olejnik, Stephen; Guo, Jiin-Huarng – Journal of Experimental Education, 2008
Formulas to determine the necessary sample sizes for parametric tests of group comparisons are available from several sources and appropriate when population distributions are normal. However, in the context of nonnormal population distributions, researchers recommend Yuen's trimmed mean test, but formulas to determine sample sizes have not been…
Descriptors: Sample Size, Computer Simulation, Statistical Analysis, Tests
Shieh, Gwowen – Psychometrika, 2007
The underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all…
Descriptors: Sample Size, Monte Carlo Methods, Multiple Regression Analysis, Statistical Analysis
Lee, Sik-Yum; Song, Xin-Yuan; Lee, John C. K. – Journal of Educational and Behavioral Statistics, 2003
The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models…
Descriptors: Structural Equation Models, Simulation, Computer Software, Computation