USE AND MISUSE OF MIXED-MODEL ANALYSIS OF VARIANCE IN ECOLOGICAL-STUDIES

Citation
Cc. Bennington et Wv. Thayne, USE AND MISUSE OF MIXED-MODEL ANALYSIS OF VARIANCE IN ECOLOGICAL-STUDIES, Ecology, 75(3), 1994, pp. 717-722
Citations number
16
Categorie Soggetti
Ecology
Journal title
ISSN journal
00129658
Volume
75
Issue
3
Year of publication
1994
Pages
717 - 722
Database
ISI
SICI code
0012-9658(1994)75:3<717:UAMOMA>2.0.ZU;2-Y
Abstract
Analysis of variance is one of the most commonly used statistical tech niques among ecologists and evolutionary biologists. Because many ecol ogical experiments involve random as well as fixed effects, the most a ppropriate analysis of variance model to use is often the mixed model. Consideration of effects in an analysis of variance as fixed or rando m is critical if correct tests are to be made and if correct inference s are to be drawn from these tests. A literature review was conducted to determine whether authors are generally aware of the differences be tween fixed and random effects and whether they are performing analyse s consistent with their consideration. All articles (excluding Notes a nd Comments) in Ecology and Evolution for the years 1990 and 1991 were reviewed.In general, authors that stated that their model contained b oth fixed and random effects correctly analyzed it as a mixed model. T here were two cases, however, where authors attempted to define fixed effects as random in order to justify broader generalizations about th e effects. Most commonly (63% of articles using two-way or greater ANO VA), authors neglected to mention whether they were dealing with a com pletely fixed, random, or mixed model. In such instances, it was not c lear if the author was aware of the distinction between fixed and rand om effects, and it was often difficult to ascertain from the article w hether their analysis was consistent with their experimental methods. These findings suggest several statistical guidelines that should be f ollowed. In particular, the inclusion of explicit consideration of eff ects as fixed or random and clear descriptions of F tests of interest would provide the reader with confidence that the author has performed the analysis correctly. In addition, such an explicit statement would clarify the limits of the inferences about significant effects.