Research Article

Analysis of longitudinal studies with death and drop-out: a case study

  1. Carole Dufouil1,*,
  2. Carol Brayne2,
  3. David Clayton3

Article first published online: 29 JUN 2004

DOI: 10.1002/sim.1821

Issue

Statistics in Medicine

Statistics in Medicine

Volume 23, Issue 14, pages 2215–2226, 30 July 2004

Additional Information

How to Cite

Dufouil, C., Brayne, C. and Clayton, D. (2004), Analysis of longitudinal studies with death and drop-out: a case study. Statistics in Medicine, 23: 2215–2226. doi: 10.1002/sim.1821

Author Information

  1. 1

    INSERM Unit 360, Hopital La Salpetriere, 75651 Paris Cedex 13, France

  2. 2

    Department of Epidemiology and Community Health, Cambridge, U.K.

  3. 3

    Cambridge Institute for Medical Research, Cambridge, U.K.

*INSERM Unit 360, Hopital La Salpetriere, 75651 Paris Cedex 13, France

Publication History

  1. Issue published online: 29 JUN 2004
  2. Article first published online: 29 JUN 2004
  3. Manuscript Accepted:
  4. Manuscript Received:

Funded by

  • The Alliance Programme. Grant Number: 00196N
  • Juvenile Diabetes Research Foundation/Wellcome Trust

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Keywords:

  • cohort studies;
  • missing data mechanism;
  • missing at random;
  • marginal models;
  • inverse probability weighting;
  • non-ignorable missingness

Abstract

The analysis of longitudinal data has recently been an active area of biostatistical research. Two main approaches to analysis have emerged, the first concentrating on modelling evolution of marginal distributions of the main response variable of interest and the other on subject-specific trajectories. In epidemiology the analysis is usually complicated by missing data and by death of study participants. Motivated by a study of cognitive decline in the elderly, this paper argues that these two types of incomplete follow-up may need to be treated differently in the analysis, and proposes an extension to the marginal modelling approach. The problem of informative drop-out is also discussed. The methods are implemented in the ‘Stata’ statistical package. Copyright © 2004 John Wiley & Sons, Ltd.

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