Abstract
The step of data analysis in a scientific work is not always a friendly universe. Here, I provide suggestions and warn of five pitfalls in a proposal of statistical routine focused on selection of predictor variables for multiple regression—a simple model used to answer questions commonly raised in Vegetation Ecology—and verification of assumptions of this method. I believe that this manuscript will clarify important points in the data analysis process and, therefore, contribute to make studies in Vegetation Ecology more competitive in the international scientific scenario.
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Notes
Here, I comment only on spatial independence, but note that there are also the temporal and phylogenetic types of independence (see, for instance, Peres Neto 2006).
Removing outliers requires a well-defined criterion (e.g., Quinn and Keough 2002). Otherwise, you can enter a bias in the significance analysis of relationships between variables.
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Acknowledgments
I thank the two anonymous reviewers for their valuable contributions. I am especially grateful to my students and also to AT Oliveira Filho and MA Cupertino, for encouraging the production of this manuscript.
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Eisenlohr, P.V. Challenges in data analysis: pitfalls and suggestions for a statistical routine in Vegetation Ecology. Braz. J. Bot 36, 83–87 (2013). https://doi.org/10.1007/s40415-013-0002-9
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DOI: https://doi.org/10.1007/s40415-013-0002-9