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Cerullo, Enzo; Jones, Hayley E.; Carter, Olivia; Quinn, Terry J.; Cooper, Nicola J.; Sutton, Alex J. – Research Synthesis Methods, 2022
Standard methods for the meta-analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal data. Within the context of an imperfect gold standard, they have previously been used for the analysis of…
Descriptors: Meta Analysis, Test Format, Medicine, Standards
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
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
Wu, Meng-Jia; Becker, Betsy Jane – Research Synthesis Methods, 2013
Regression methods are widely used by researchers in many fields, yet methods for synthesizing regression results are scarce. This study proposes using a factored likelihood method, originally developed to handle missing data, to appropriately synthesize regression models involving different predictors. This method uses the correlations reported…
Descriptors: Regression (Statistics), Correlation, Research Methodology, Accuracy