Premium
Randomization methods and the analysis of multivariate ecological data
Author(s) -
Smith Eric P.
Publication year - 1998
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/(sici)1099-095x(199801/02)9:1<37::aid-env284>3.0.co;2-t
Subject(s) - multivariate statistics , normality , test statistic , statistic , multivariate analysis of variance , computer science , multivariate analysis , statistics , test (biology) , econometrics , restricted randomization , resampling , randomization , statistical hypothesis testing , mathematics , ecology , clinical trial , biology , bioinformatics
Abstract Data from ecological and biomonitoring studies are sometimes difficult to make inferences from owing to the high dimensionality of the data, the lack of normality and other problems. One approach for testing which has interested researchers is the randomization method. A general approach is based on replacing the multivariate data with distances between units, choosing a test statistic to summarize differences (due say to a treatment) and using a randomization test to assess the significance of the differences. This paper discusses a number of questions and concerns related to analysis and interpretation using this analytical approach. First, what can be said about the power of this test and how is the power related to the power of other tests under optimal conditions? Second, the variables (species) seem to get lost in the analysis. How important are they and should one be concerned about their importance to the power of the test? Finally, how important are assumptions about the data? These questions and others are discussed using examples from multispecies studies. © 1998 John Wiley & Sons, Ltd.