Multiple imputation for estimation of an occurrence rate in cohorts with attrition and discrete follow-up time points: a simulation study.
BMC Med Res Methodol
; 10: 79, 2010 Sep 03.
Article
em En
| MEDLINE
| ID: mdl-20815883
ABSTRACT
BACKGROUND:
In longitudinal cohort studies, subjects may be lost to follow-up at any time during the study. This leads to attrition and thus to a risk of inaccurate and biased estimations. The purpose of this paper is to show how multiple imputation can take advantage of all the information collected during follow-up in order to estimate the cumulative probability P(E) of an event E, when the first occurrence of this event is observed at t successive time points of a longitudinal study with attrition.METHODS:
We compared the performance of multiple imputation with that of Kaplan-Meier estimation in several simulated attrition scenarios.RESULTS:
In missing-completely-at-random scenarios, the multiple imputation and Kaplan-Meier methods performed well in terms of bias (less than 1%) and coverage rate (range = [94.4%; 95.8%]). In missing-at-random scenarios, the Kaplan-Meier method was associated with a bias ranging from -5.1% to 7.0% and with a very poor coverage rate (as low as 0.2%). Multiple imputation performed much better in this situation (bias <2%, coverage rate >83.4%).CONCLUSIONS:
Multiple imputation shows promise for estimation of an occurrence rate in cohorts with attrition. This study is a first step towards defining appropriate use of multiple imputation in longitudinal studies.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Médicos de Família
/
Polimedicação
Tipo de estudo:
Observational_studies
/
Qualitative_research
/
Risk_factors_studies
Limite:
Adult
/
Humans
/
Middle aged
País/Região como assunto:
Europa
Idioma:
En
Revista:
BMC Med Res Methodol
Assunto da revista:
MEDICINA
Ano de publicação:
2010
Tipo de documento:
Article
País de afiliação:
França