Simple t-distribution Based Tests for Meta-Analysis
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Date
1999
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Universitätsbibliothek Dortmund
Abstract
The variance function of the optimal estimator of the overall mean in a heteroscedastic one-way ANOVA model is dominated by positive semi-definite quadratic functions. This makes it possible to develop closely related tests on the nullity of the overall mean parameter, in one-way fifixed and random effects ANOVA models, which make use of the quantiles of the t-distribution. These tests are founded on the convexity arguments similar to Hartung (1976). Simulation results indicate that the proposed tests attain type I error rates which are far more acceptable than those of the commonly used tests.
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Keywords
balanced and unbalanced samples, estimated degrees of freedom, fixed and random effects models, homoscedastic and heteroscedastic error variances, replication, type I error rate