This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Hogan, J. W Articles by Laird, N. M Search for Related Content PubMed PubMed Citation Articles by Hogan, J. W Articles by Laird, N. M Social Bookmarking                   What's this?

Increasing efficiency from censored survival data by using random effects to model longitudinal covariates

Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA, jhogan{at}stat.brown.edu

Nan M Laird

Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA

When estimating a survival time distribution, the loss of information due to right censoring results in a loss of efficiency in the estimator. In many circumstances, however, repeated measurements on a longitudinal process which is associated with survival time are made throughout the observation time, and these measurements may be used to recover information lost to censoring. For example, patients in an AIDS clinical trial may be measured at regular intervals on CD4 count and viral load.

We describe a model for the joint distribution of a survival time and a repeated measures process. The joint distribution is specified by linking the survival time to subject-specific random effects characterizing the repeated measures, and is similar in form to the pattern mixture model for multivariate data with nonignorable nonresponse. We also describe an estimator of survival derived from this model.

We apply the methods to a long-term AIDS clinical trial, and study properties of the survival estimator. Monte Carlo simulation is used to estimate gains in efficiency when the survival time is related to the location and scale of the random effects distribution. Under relatively light censoring (20%), the methods yield a modest gain in efficiency for estimating three-year survival in the AIDS clinical trial. Our simulation study, which mimics characteristics of the clinical trial, indicates that much larger gains in efficiency can be realized under heavier censoring or with studies designed for long term follow up on survival.

Statistical Methods in Medical Research, Vol. 7, No. 1, 28-48 (1998)
DOI: 10.1177/096228029800700104


CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?

This article has been cited by other articles:

				J. M Albert and H. Yun Statistical advances in AIDS therapy trials Statistical Methods in Medical Research, April 1, 2001; 10(2): 85 - 100. [Abstract] [PDF]

				N. G Becker and I. C Marschner Advances in medical statistics arising from the AIDS epidemic Statistical Methods in Medical Research, April 1, 2001; 10(2): 117 - 140. [Abstract] [PDF]