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Direct linkQi, Hongchao; Rizopoulos, Dimitris; Rosmalen, Joost – Research Synthesis Methods, 2023
The meta-analytic-predictive (MAP) approach is a Bayesian method to incorporate historical controls in new trials that aims to increase the statistical power and reduce the required sample size. Here we investigate how to calculate the sample size of the new trial when historical data is available, and the MAP approach is used in the analysis. In…
Descriptors: Sample Size, Computation, Meta Analysis, Bayesian Statistics
Hong, Sanghyun; Reed, W. Robert – Research Synthesis Methods, 2021
The purpose of this study is to show how Monte Carlo analysis of meta-analytic estimators can be used to select estimators for specific research situations. Our analysis conducts 1620 individual experiments, where each experiment is defined by a unique combination of sample size, effect size, effect size heterogeneity, publication selection…
Descriptors: Monte Carlo Methods, Meta Analysis, Research Methodology, Experiments
Gnambs, Timo; Staufenbiel, Thomas – Research Synthesis Methods, 2016
Two new methods for the meta-analysis of factor loadings are introduced and evaluated by Monte Carlo simulations. The direct method pools each factor loading individually, whereas the indirect method synthesizes correlation matrices reproduced from factor loadings. The results of the two simulations demonstrated that the accuracy of…
Descriptors: Accuracy, Meta Analysis, Factor Structure, Monte Carlo Methods
