Recommended effect size statistics for repeated measures designs

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Recommended effect size statistics for repeated measures designs.

Investigators, who are increasingly implored to present and discuss effect size statistics, might comply more often if they understood more clearly what is required. When investigators wish to report effect sizes derived from analyses of variance that include repeated measures, past advice has been problematic. Only recently has a generally useful effect size statistic been proposed for such de...

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Generalized eta and omega squared statistics: measures of effect size for some common research designs.

The editorial policies of several prominent educational and psychological journals require that researchers report some measure of effect size along with tests for statistical significance. In analysis of variance contexts, this requirement might be met by using eta squared or omega squared statistics. Current procedures for computing these measures of effect often do not consider the effect th...

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HE Plots for Repeated Measures Designs

Hypothesis error (HE) plots, introduced in Friendly (2007), provide graphical methods to visualize hypothesis tests in multivariate linear models, by displaying hypothesis and error covariation as ellipsoids and providing visual representations of effect size and significance. These methods are implemented in the heplots for R (Fox, Friendly, and Monette 2009a) and SAS (Friendly 2006), and appl...

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Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs.

When a meta-analysis on results from experimental studies is conducted, differences in the study design must be taken into consideration. A method for combining results across independent-groups and repeated measures designs is described, and the conditions under which such an analysis is appropriate are discussed. Combining results across designs requires that (a) all effect sizes be transform...

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Testing multiple outcomes in repeated measures designs.

This study investigates procedures for controlling the familywise error rate (FWR) when testing hypotheses about multiple, correlated outcome variables in repeated measures (RM) designs. A content analysis of RM research articles published in 4 psychology journals revealed that 3 quarters of studies tested hypotheses about 2 or more outcome variables. Several procedures originally proposed for ...

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ژورنال

عنوان ژورنال: Behavior Research Methods

سال: 2005

ISSN: 1554-351X,1554-3528

DOI: 10.3758/bf03192707