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Bonett, Douglas G. – Journal of Educational and Behavioral Statistics, 2015
Paired-samples designs are used frequently in educational and behavioral research. In applications where the response variable is quantitative, researchers are encouraged to supplement the results of a paired-samples t-test with a confidence interval (CI) for a mean difference or a standardized mean difference. Six CIs for standardized mean…
Descriptors: Educational Research, Sample Size, Statistical Analysis, Effect Size
Wanstrom, Linda – Multivariate Behavioral Research, 2009
Second-order latent growth curve models (S. C. Duncan & Duncan, 1996; McArdle, 1988) can be used to study group differences in change in latent constructs. We give exact formulas for the covariance matrix of the parameter estimates and an algebraic expression for the estimation of slope differences. Formulas for calculations of the required sample…
Descriptors: Sample Size, Effect Size, Mathematical Formulas, Computation
Gilpin, Andrew R. – Educational and Psychological Measurement, 2008
Rosenthal and Rubin introduced a general effect size index, r[subscript equivalent], for use in meta-analyses of two-group experiments; it employs p values from reports of the original studies to determine an equivalent t test and the corresponding point-biserial correlation coefficient. The present investigation used Monte Carlo-simulated…
Descriptors: Effect Size, Correlation, Meta Analysis, Monte Carlo Methods
Aaron, Bruce C.; Kromrey, Jeffrey D. – 1998
In a Monte Carlo analysis of single-subject data, Type I and Type II error rates were compared for various statistical tests of the significance of treatment effects. Data for 5,000 subjects in each of 6 treatment effect size groups were computer simulated, and 2 types of treatment effects were simulated in the dependent variable during…
Descriptors: Computer Simulation, Effect Size, Monte Carlo Methods, Nonparametric Statistics
Barnette, J. Jackson; McLean, James E. – 2000
The probabilities of attaining varying magnitudes of standardized effect sizes by chance and when protected by a 0.05 level statistical test were studied. Monte Carlo procedures were used to generate standardized effect sizes in a one-way analysis of variance situation with 2 through 5, 6, 8, and 10 groups with selected sample sizes from 5 to 500.…
Descriptors: Computer Simulation, Effect Size, Monte Carlo Methods, Probability
Peer reviewedLaw, Kenneth S. – Journal of Educational and Behavioral Statistics, 1995
Two new methods of estimating the mean population correlation (M) and the standard deviation of population correlations (SD) were suggested and tested by Monte Carlo simulations. Results show no consistent advantage to using the Pearson correlation or Fisher's Z in estimating M or SD; estimates from all methods are similar. (SLD)
Descriptors: Computer Simulation, Correlation, Effect Size, Estimation (Mathematics)
Reynolds, Sharon; Day, Jim – 1984
Monte Carlo studies explored the sampling characteristics of Cohen's d and three approximations to Cohen's d when used as average effect size measures in meta-analysis. Reviews of 10, 100, and 500 studies (M) were simulated, with degrees of freedom (df) varied in seven steps from 8 to 58. In a two independent groups design, samples were obtained…
Descriptors: Computer Simulation, Effect Size, Estimation (Mathematics), Meta Analysis
Peer reviewedCornwell, John M.; Ladd, Robert T. – Educational and Psychological Measurement, 1993
Simulated data typical of those from meta analyses are used to evaluate the reliability, Type I and Type II errors, bias, and standard error of the meta-analytic procedures of Schmidt and Hunter (1977). Concerns about power, reliability, and Type I errors are presented. (SLD)
Descriptors: Bias, Computer Simulation, Correlation, Effect Size

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