Royston, P;
(2014)
A smooth covariate rank transformation for use in regression models with a sigmoid dose-response function.
Stata Journal
, 14
(2)
329 - 341.
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Abstract
We consider how to represent sigmoid-type regression relationships in a practical and parsimonious way. A pure sigmoid relationship has an asymptote at both ends of the range of a continuous covariate. Curves with a single asymptote are also important in practice. Many smoothers, such as fractional polynomials and restricted cubic regression splines, cannot accurately represent doubly asymptotic curves. Such smoothers may struggle even with singly asymptotic curves. Our approach to modeling sigmoid relationships involves applying a preliminary scaled rank transformation to compress the tails of the observed distribution of a continuous covariate. We include a step that provides a smooth approximation to the empirical cumulative distribution function of the covariate via the scaled ranks. The procedure defines the approximate cumulative distribution transformation of the covariate. To fit the substantive model, we apply fractional polynomial regression to the outcome with the smoothed, scaled ranks as the covariate. When the resulting fractional polynomial function is monotone, we have a sigmoid function. We demonstrate several practical applications of the approximate cumulative distribution transformation while also illustrating its ability to model some unusual functional forms. We describe a command, acd, that implements it.
| Type: | Article |
|---|---|
| Title: | A smooth covariate rank transformation for use in regression models with a sigmoid dose-response function |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://www.stata-journal.com/article.html?article=... |
| Language: | English |
| Additional information: | Copyright © 2014 by StataCorp LP The Stata Journal and the contents of the supporting files (programs, datasets, and help files) are copyright © by StataCorp LP. The contents of the supporting files (progra ms, datasets, and help files) may be copied or reproduced by any means whatsoever, in whole or in part, as long as any copy or reproduction includes attribution to both (1) the author and (2) the Stata Journal. The articles appearing in the Stata Journal may be copied or reproduced as printed copies, in whole or in part, as long as any copy or reproduction includes attribution to both (1) the author and (2) the Stata Journal. Written permission must be obtained from StataCorp if you wish to make electronic copies of the insertions. This precludes placing electronic copies of the Stata Journal, in whole or in part, on publicly accessible websites, fileservers, or other locations where the copy may be accessed by anyone other than the subscriber. |
| Keywords: | ACD, continuous covariate, sigmoid function, fractional polynomials, regression models |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1433543 |
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