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Direct linkPoom, Leo; af Wåhlberg, Anders – Research Synthesis Methods, 2022
In meta-analysis, effect sizes often need to be converted into a common metric. For this purpose conversion formulas have been constructed; some are exact, others are approximations whose accuracy has not yet been systematically tested. We performed Monte Carlo simulations where samples with pre-specified population correlations between the…
Descriptors: Meta Analysis, Effect Size, Mathematical Formulas, Monte Carlo Methods
Smith, Julie M. – ProQuest LLC, 2011
This study examines the proposed Reliability Generalization (RG) method for studying reliability. RG employs the application of meta-analytic techniques similar to those used in validity generalization studies to examine reliability coefficients. This study explains why RG does not provide a proper research method for the study of reliability,…
Descriptors: Reliability, Generalization, Sampling, Research Methodology
Williams, J. Michael; Cottle, Cindy C. – Psychological Assessment, 2011
Normative comparisons are an integral component of neuropsychological test interpretation and provide the basis for an inference of abnormal function and impairment. In order to remedy a deficit of normative standards for a large number of neuropsychology tests, Mitrushina, Boone, Razani, and D'Elia (2005) used the meta-analysis of studies that…
Descriptors: Meta Analysis, Test Norms, Intelligence Tests, Statistical Bias
Sanchez-Meca, Julio; Marin-Martinez, Fulgencio – Psychological Methods, 2008
One of the main objectives in meta-analysis is to estimate the overall effect size by calculating a confidence interval (CI). The usual procedure consists of assuming a standard normal distribution and a sampling variance defined as the inverse of the sum of the estimated weights of the effect sizes. But this procedure does not take into account…
Descriptors: Intervals, Monte Carlo Methods, Meta Analysis, Effect Size
Viechtbauer, Wolfgang – Journal of Educational and Behavioral Statistics, 2005
The meta-analytic random effects model assumes that the variability in effect size estimates drawn from a set of studies can be decomposed into two parts: heterogeneity due to random population effects and sampling variance. In this context, the usual goal is to estimate the central tendency and the amount of heterogeneity in the population effect…
Descriptors: Bias, Meta Analysis, Models, Effect Size
Download full textReynolds, 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
