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Model selection for univariable fractional polynomials

Author

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  • Patrick Royston

    (University College London)

Abstract

Since Royston and Altman’s 1994 publication (Journal of the Royal Statistical Society, Series C 43: 429–467), fractional polynomials have steadily gained popularity as a tool for flexible parametric modeling of regression relation- ships. In this article, I present fp select, a postestimation tool for fp that allows the user to select a parsimonious fractional polynomial model according to a closed test procedure called the fractional polynomial selection procedure or function se- lection procedure. I also give a brief introduction to fractional polynomial models and provide examples of using fp and fp select to select such models with real data.

Suggested Citation

  • Patrick Royston, 2017. "Model selection for univariable fractional polynomials," Stata Journal, StataCorp LP, vol. 17(3), pages 619-629, September.
    • Handle: RePEc:tsj:stataj:y:17:y:2017:i:3:p:619-629
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    Cited by:

    1. Tim Wallrafen & Georgios Nalbantis & Tim Pawlowski, 2022. "Competition and Fan Substitution Between Professional Sports Leagues," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 61(1), pages 21-43, August.
    2. Norah Alosaimi & Eduardo Bernabé, 2022. "Amount and Frequency of Added Sugars Intake and Their Associations with Dental Caries in United States Adults," IJERPH, MDPI, vol. 19(8), pages 1-9, April.

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