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STATISTICAL ISSUES IN ECOLOGICAL META‐ANALYSES
Author(s) -
Gurevitch Jessica,
Hedges Larry V.
Publication year - 1999
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/0012-9658(1999)080[1142:siiema]2.0.co;2
Subject(s) - categorical variable , resampling , heteroscedasticity , statistics , variance (accounting) , ecology , meta analysis , sampling (signal processing) , econometrics , regression analysis , type i and type ii errors , computer science , mathematics , biology , medicine , accounting , filter (signal processing) , business , computer vision
Meta‐analysis is the use of statistical methods to summarize research findings across studies. Special statistical methods are usually needed for meta‐analysis, both because effect‐size indexes are typically highly heteroscedastic and because it is desirable to be able to distinguish between‐study variance from within‐study sampling‐error variance. We outline a number of considerations related to choosing methods for the meta‐analysis of ecological data, including the choice of parametric vs. resampling methods, reasons for conducting weighted analyses where possible, and comparisons fixed vs. mixed models in categorical and regression‐type analyses.