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Practical Use of the Information-Theoretic Approach

In: Model Selection and Inference

Author

Listed:
  • Kenneth P. Burnham

    (Colorado State University, Colorado Cooperative Fish and Wildlife Research Unit)

  • David R. Anderson

    (Colorado State University, Colorado Cooperative Fish and Wildlife Research Unit)

Abstract

Model building and data analysis in the biological sciences somewhat presupposes that the person has some advanced education in the quantitative sciences, and statistics in particular. This requirement also implies that a person has substantial knowledge of statistical hypothesis-testing approaches. Such people, including ourselves over the past several years, often find it difficult to understand the information-theoretic approach, only because it is conceptually so very different from the testing approach that is so familiar. Relatively speaking, the concepts and practical use of the information-theoretic approach are much simpler than those of statistical hypothesis testing, and very much simpler than some of the various Bayesian approaches to data analysis (e.g., Laud and Ibrahim 1995 and Carlin and Chib 1995).

Suggested Citation

  • Kenneth P. Burnham & David R. Anderson, 1998. "Practical Use of the Information-Theoretic Approach," Springer Books, in: Model Selection and Inference, chapter 3, pages 75-117, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-2917-7_3
    DOI: 10.1007/978-1-4757-2917-7_3
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    Cited by:

    1. Vincenzo Basile & Luana Serino & Antonello D’ Ambra & Francesco Campanella, 2026. "Board characteristics and effects on ESG performance: empirical evidence from the European banking system," Quality & Quantity: International Journal of Methodology, Springer, vol. 60(1), pages 2121-2138, February.

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