Semiparametric regression analysis of longitudinal data with informative observation times

Jianguo Sun, Do Hwan Park, Liuquan Sun, Xingqiu Zhao

Research output: Journal article publicationReview articleAcademic researchpeer-review

72 Citations (Scopus)

Abstract

Statistical analysis of longitudinal data has been discussed by many authors, and a number of methods have been proposed. Most of the research have focused on situations where observation times are independent of or carry no information about the response variable and therefore rely on conditional inference procedures given the observation times. This article considers a different situation, where the independence assumption may not hold; that is, the observation times may carry information about the response variable. For inference, estimating equation approaches are proposed, and both large-sample and final-sample properties of the proposed methods are established. The methodology is applied to a bladder cancer study that motivated this investigation.
Original languageEnglish
Pages (from-to)882-889
Number of pages8
JournalJournal of the American Statistical Association
Volume100
Issue number471
DOIs
Publication statusPublished - 1 Sept 2005
Externally publishedYes

Keywords

  • Estimating equation
  • Informative observation times
  • Longitudinal data
  • Nonhomogeneous Poisson process

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Fingerprint

Dive into the research topics of 'Semiparametric regression analysis of longitudinal data with informative observation times'. Together they form a unique fingerprint.

Cite this