Expressing Estimators of Expected Quality Adjusted Survival as Functions of Nelson-Aalen Estimators

Yijian Huang, Thomas A. Louis

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Quality adjusted survival has been increasingly advocated in clinical trials to be assessed as a synthesis of survival and quality of life. We investigate nonparametric estimation of its expectation for a general multistate process with incomplete follow-up data. Upon establishing a representation of expected quality adjusted survival through marginal distributions of a set of defined events, we propose two estimators for expected quality adjusted survival. Expressed as functions of Nelson-Aalen estimators, the two estimators are strongly consistent and asymptotically normal. We derive their asymptotic variances and propose sample-based variance estimates, along with evaluation of asymptotic relative efficiency. Monte Carlo studies show that these estimation procedures perform well for practical sample sizes. We illustrate the methods using data from a national, multicenter AIDS clinical trial.

Original languageEnglish (US)
Pages (from-to)199-212
Number of pages14
JournalLifetime Data Analysis
Issue number3
StatePublished - 1999
Externally publishedYes


  • Counting process
  • Martingale
  • Multistate process
  • Multivariate failure time
  • Nonparametric method

ASJC Scopus subject areas

  • Applied Mathematics


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