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Comput Methods Programs Biomed. 2004 Jul;75(1):45-9.

Adjusted survival curves with inverse probability weights.

Author information

  • 1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street E-7014, Baltimore, MD 21205, USA. scole@jhu.edu

Abstract

Kaplan-Meier survival curves and the associated nonparametric log rank test statistic are methods of choice for unadjusted survival analyses, while the semiparametric Cox proportional hazards regression model is used ubiquitously as a method for covariate adjustment. The Cox model extends naturally to include covariates, but there is no generally accepted method to graphically depict adjusted survival curves. The authors describe a method and provide a simple worked example using inverse probability weights (IPW) to create adjusted survival curves. When the weights are non-parametrically estimated, this method is equivalent to direct standardization of the survival curves to the combined study population.

PMID:
15158046
[PubMed - indexed for MEDLINE]
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