Published in

Wiley, Pharmacoepidemiology & Drug Safety, 3(20), p. 317-320, 2010

DOI: 10.1002/pds.2074

Links

Tools

Export citation

Search in Google Scholar

The role of the c-statistic in variable selection for propensity score models

Journal article published in 2010 by Daniel Westreich ORCID, Stephen R. Cole, Michele Jonsson Funk, M. Alan Brookhart, Til Stürmer
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Upload
Orange circle
Postprint: archiving restricted
Upload
Red circle
Published version: archiving forbidden
Policy details
Data provided by SHERPA/RoMEO

Abstract

The applied literature on propensity scores has often cited the c-statistic as a measure of the ability of the propensity score to control confounding. However, a high c-statistic in the propensity model is neither necessary nor sufficient for control of confounding. Moreover, use of the c-statistic as a guide in constructing propensity scores may result in less overlap in propensity scores between treated and untreated subjects; this may require the analyst to restrict populations for inference. Such restrictions may reduce precision of estimates and change the population to which the estimate applies. Variable selection based on prior subject matter knowledge, empirical observation, and sensitivity analysis is preferable and avoids many of these problems.