Multiple outputation for the analysis of longitudinal data subject to irregular observation.

Abstract:

:Observational cohort studies often feature longitudinal data subject to irregular observation. Moreover, the timings of observations may be associated with the underlying disease process and must thus be accounted for when analysing the data. This paper suggests that multiple outputation, which consists of repeatedly discarding excess observations, may be a helpful way of approaching the problem. Multiple outputation was designed for clustered data where observations within a cluster are exchangeable; an adaptation for longitudinal data subject to irregular observation is proposed. We show how multiple outputation can be used to expand the range of models that can be fitted to irregular longitudinal data.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Pullenayegum EM

doi

10.1002/sim.6829

subject

Has Abstract

pub_date

2016-05-20 00:00:00

pages

1800-18

issue

11

eissn

0277-6715

issn

1097-0258

journal_volume

35

pub_type

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