A practical guide to selecting models for exploration, inference, and prediction in ecology.

ABSTRACT: Selecting among competing statistical models is a core challenge in science. However, the many possible approaches and techniques for model selection, and the conflicting recommendations for their use, can be confusing. We contend that much confusion surrounding statistical model selection results from failing to first clearly specify the purpose of the analysis. We argue that there are three distinct goals for statistical modeling in ecology: data exploration, inference, and prediction. Once the modeling goal is clearly articulated, an appropriate model selection procedure is easier to identify. We review model selection approaches and highlight their strengths and weaknesses relative to each of the three modeling goals. We then present examples of modeling for exploration, inference, and

SUBMITTER: Tredennick AT 

PROVIDER: S-EPMC8187274 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature