Slope estimation in the presence of informative right censoring: modeling the number of observations as a geometric random variable.

Published

Journal Article

A method is proposed for the estimation of rate of change from incomplete longitudinal data where the number of observations made for each subject is assumed to vary depending on the level of the response variable. The proposed method involves a random slope model, in which the number of observations is modeled as a geometric distribution with its mean dependent on the individual subject's rate of change. The method adjusts for informative right censoring and provides estimates of the slopes of individual subjects as well as of the population. Under noninformative right censoring these estimators of the slopes are equivalent to Bayes estimators (Fearn, 1975, Biometrika 62, 89-100). The simulation study demonstrates that, in cases where the censoring process is informative, the proposed estimator is more efficient than either the unweighted or weighted estimator of slope. The method is illustrated by the analysis of renal transplant data.

Full Text

Cited Authors

  • Mori, M; Woolson, RF; Woodworth, GG

Published Date

  • March 1994

Published In

Volume / Issue

  • 50 / 1

Start / End Page

  • 39 - 50

PubMed ID

  • 8086614

Pubmed Central ID

  • 8086614

Electronic International Standard Serial Number (EISSN)

  • 1541-0420

International Standard Serial Number (ISSN)

  • 0006-341X

Digital Object Identifier (DOI)

  • 10.2307/2533195

Language

  • eng