Regression and model-building in conservation biology, biogeography and ecology: The distinction between – and reconciliation of – ‘predictive’ and ‘explanatory’ ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2000-05

AUTHORS

Ralph Mac Nally

ABSTRACT

In many large-scale conservation or ecological problems where experiments are intractable or unethical, regression methods are used to attempt to gauge the impact of a set of nominally independent variables (X) upon a dependent variable (Y). Workers often want to assert that a given X has a major influence on Y, and so, by using this indirection to infer a probable causal relationship. There are two difficulties apart from the demonstrability issue itself: (1) multiple regression is plagued by collinear relationships in X; and (2) any regression is designed to produce a function that in some way minimizes the overall difference between the observed and ‘predicted’ Ys, which does not necessarily equate to determining probable influence in a multivariate setting. Problem (1) may be explored by comparing two avenues, one in which a single ‘best’ regression model is sought and the other where all possible regression models are considered contemporaneously. It is suggested that if the two approaches do not agree upon which of the independent variables are likely to be ‘significant’, then the deductions must be subject to doubt. More... »

PAGES

655-671

References to SciGraph publications

Journal

TITLE

Biodiversity and Conservation

ISSUE

5

VOLUME

9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1008985925162

DOI

http://dx.doi.org/10.1023/a:1008985925162

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1044106770


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