A comparison of methods to adjust for continuous covariates in the analysis of randomised trials

Kahan, Brennan C., Rushton, Helen, Morris, Tim P. and Daniel, Rhian ORCID: https://orcid.org/0000-0001-5649-9320 2016. A comparison of methods to adjust for continuous covariates in the analysis of randomised trials. BMC Medical Research Methodology 16 , 42. 10.1186/s12874-016-0141-3

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (681kB) | Preview

Abstract

Background Although covariate adjustment in the analysis of randomised trials can be beneficial, adjustment for continuous covariates is complicated by the fact that the association between covariate and outcome must be specified. Misspecification of this association can lead to reduced power, and potentially incorrect conclusions regarding treatment efficacy. Methods We compared several methods of adjustment to determine which is best when the association between covariate and outcome is unknown. We assessed (a) dichotomisation or categorisation; (b) assuming a linear association with outcome; (c) using fractional polynomials with one (FP1) or two (FP2) polynomial terms; and (d) using restricted cubic splines with 3 or 5 knots. We evaluated each method using simulation and through a re-analysis of trial datasets. Results Methods which kept covariates as continuous typically had higher power than methods which used categorisation. Dichotomisation, categorisation, and assuming a linear association all led to large reductions in power when the true association was non-linear. FP2 models and restricted cubic splines with 3 or 5 knots performed best overall. Conclusions For the analysis of randomised trials we recommend (1) adjusting for continuous covariates even if their association with outcome is unknown; (2) keeping covariates as continuous; and (3) using fractional polynomials with two polynomial terms or restricted cubic splines with 3 to 5 knots when a linear association is in doubt.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine
Subjects:	R Medicine > R Medicine (General)
Uncontrolled Keywords:	Randomised controlled trial; Covariate adjustment; Continuous variables; Fractional polynomials; Restricted cubic splines
Publisher:	BioMed Central
ISSN:	1471-2288
Date of First Compliant Deposit:	15 November 2017
Date of Acceptance:	1 April 2016
Last Modified:	06 May 2023 05:38
URI:	https://orca.cardiff.ac.uk/id/eprint/106067

Citation Data

Cited 27 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item