Matlab code to perform factorial meta-analyses using Hedges'.dand the log response ratio.E088-063-S2

Ecological Archives

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William F. Morris

Department of Biology

Duke University

Box 90338

Durham, NC 27708-0338 USA

E-mail: wfmorris@duke.edu

meta_fact.zip -- zip file containing the following eight MATLAB function files:

fact_hedges_d.m -- A Matlab function that returns the individual, overall, and interaction effect sizes for 2 "agents" in a 2 × 2 factorial experiment, where effect size is measured using Hedges'

d; the sampling variances of each effect size are also returned.fact_logRR.m -- A Matlab function that returns the individual, overall, and interaction effect sizes for 2 "agents" in a 2 × 2 factorial experiment, where effect size is measured using the log response ratio; the sampling variances and degrees of freedom of each effect size are also returned.

J.m -- A Matlab function that computes the small-sample size correction factor J.

Q.m -- A Matlab function that computes a weighted sum of squares.

mean_effect.m -- A Matlab function that returns a weighted mean effect size and its 95% confidence limits, where the weights include the among-study variance if it is significant at

P< 0.05. Best used when effect sizes are measured using Hedges' d; for the log response ratio, use mean_effect_L.mean_effect_L.m -- A Matlab function that returns the weighted mean log response ratio effect size, its SE, and its 95% confidence limits, where the weights include the among-study variance, the significance of which (from a chi-square test on the sum of squares) is returned as well.

test_Qb_mixed_2.m -- A Matlab function that tests for a significant between-class sum of squares in a mixed-model meta-analysis comparing two classes.

test_Qb_mixed_n.m -- A Matlab function that tests for a significant between-class sum of squares in a mixed-model meta-analysis comparing n classes.

This supplement includes Matlab code to compute individual, overall, and interactive effects using Hedges’

dand the log response ratio, to calculate weighted mean effect sizes, and to perform mixed-model homogeneity tests.Functions mean_effect, mean_effect_L, test_Qb_mixed_2, and test_Qb_mixed_n all use the function chi2cdf from the Matlab Statistics Toolbox. Additional documentation appears as comments at the beginning of each function file; once the files have been downloaded into a folder in the Matlab path, typing help function_name (e.g., help fact_logRR) at the Matlab command prompt will display the descriptive comments.

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