Model selection for univariable fractional polynomials
Since Royston and Altman's 1994 publication ( 43: 429-467), fractional polynomials have steadily gained popularity as a tool for flexible parametric modeling of regression relationships. In this article, I present fp_select, a postestimation tool for fp that allows the user to select a parsimon...
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| Vydáno v: | The Stata journal Ročník 17; číslo 3; s. 619 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
01.09.2017
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| ISSN: | 1536-867X |
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| Abstract | Since Royston and Altman's 1994 publication (
43: 429-467), fractional polynomials have steadily gained popularity as a tool for flexible parametric modeling of regression relationships. 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 selection 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. |
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| AbstractList | Since Royston and Altman's 1994 publication (
43: 429-467), fractional polynomials have steadily gained popularity as a tool for flexible parametric modeling of regression relationships. 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 selection 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. 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 relationships. 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 selection 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.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 relationships. 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 selection 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. |
| Author | Royston, Patrick |
| Author_xml | – sequence: 1 givenname: Patrick surname: Royston fullname: Royston, Patrick organization: MRC Clinical Trials Unit, University College London, London, UK |
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| Keywords | model selection st0488 continuous covariate fractional polynomials fp_select regression models |
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43: 429-467), fractional polynomials have steadily gained popularity as a tool for flexible parametric modeling... Since Royston and Altman's 1994 publication (Journal of the Royal Statistical Society, Series C 43: 429-467), fractional polynomials have steadily gained... |
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| Title | Model selection for univariable fractional polynomials |
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