Model Selection: An Integral Part of Inference

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ID: 291558
1997
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Abstract
We argue that model selection uncertainty should be fully incorporated into statistical inference whenever estimation is sensitive to model choice and that choice is made with reference to the data. We consider different philosophies for achieving this goal and suggest strategies for data analysis. We illustrate our methods through three examples. The first is a Poisson regression of bird counts in which a choice is to be made between inclusion of one or both of two covariates. The second is a line transect data set for which different models yield substantially different estimates of abundance. The third is a simulated example in which truth is known.
Reference Key
openalex_W1994672023 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors S. T. Buckland, Kenneth P. Burnham, Nicole H. Augustin
Journal biometrics
Year 1997
DOI
10.2307/2533961
URL
https://doi.org/10.2307/2533961
Keywords Keywords not found

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