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Qi, 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
Poom, 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
Huang, Hening – Research Synthesis Methods, 2023
Many statistical methods (estimators) are available for estimating the consensus value (or average effect) and heterogeneity variance in interlaboratory studies or meta-analyses. These estimators are all valid because they are developed from or supported by certain statistical principles. However, no estimator can be perfect and must have error or…
Descriptors: Statistical Analysis, Computation, Measurement Techniques, Meta Analysis