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Analysis of longitudinal studies with death and drop‐out: a case study
Author(s) -
Dufouil Carole,
Brayne Carol,
Clayton David
Publication year - 2004
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1821
Subject(s) - computer science , missing data , drop out , econometrics , statistical analysis , r package , longitudinal data , extension (predicate logic) , statistics , data science , data mining , mathematics , machine learning , economics , demographic economics , programming language
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.