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Published in: BMC Medical Research Methodology 1/2012

Open Access 01-12-2012 | Research article

A review of the reporting and handling of missing data in cohort studies with repeated assessment of exposure measures

Authors: Amalia Karahalios, Laura Baglietto, John B Carlin, Dallas R English, Julie A Simpson

Published in: BMC Medical Research Methodology | Issue 1/2012

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Abstract

Background

Retaining participants in cohort studies with multiple follow-up waves is difficult. Commonly, researchers are faced with the problem of missing data, which may introduce biased results as well as a loss of statistical power and precision. The STROBE guidelines von Elm et al. (Lancet, 370:1453-1457, 2007); Vandenbroucke et al. (PLoS Med, 4:e297, 2007) and the guidelines proposed by Sterne et al. (BMJ, 338:b2393, 2009) recommend that cohort studies report on the amount of missing data, the reasons for non-participation and non-response, and the method used to handle missing data in the analyses. We have conducted a review of publications from cohort studies in order to document the reporting of missing data for exposure measures and to describe the statistical methods used to account for the missing data.

Methods

A systematic search of English language papers published from January 2000 to December 2009 was carried out in PubMed. Prospective cohort studies with a sample size greater than 1,000 that analysed data using repeated measures of exposure were included.

Results

Among the 82 papers meeting the inclusion criteria, only 35 (43%) reported the amount of missing data according to the suggested guidelines. Sixty-eight papers (83%) described how they dealt with missing data in the analysis. Most of the papers excluded participants with missing data and performed a complete-case analysis (n = 54, 66%). Other papers used more sophisticated methods including multiple imputation (n = 5) or fully Bayesian modeling (n = 1). Methods known to produce biased results were also used, for example, Last Observation Carried Forward (n = 7), the missing indicator method (n = 1), and mean value substitution (n = 3). For the remaining 14 papers, the method used to handle missing data in the analysis was not stated.

Conclusions

This review highlights the inconsistent reporting of missing data in cohort studies and the continuing use of inappropriate methods to handle missing data in the analysis. Epidemiological journals should invoke the STROBE guidelines as a framework for authors so that the amount of missing data and how this was accounted for in the analysis is transparent in the reporting of cohort studies.
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Metadata
Title
A review of the reporting and handling of missing data in cohort studies with repeated assessment of exposure measures
Authors
Amalia Karahalios
Laura Baglietto
John B Carlin
Dallas R English
Julie A Simpson
Publication date
01-12-2012
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2012
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/1471-2288-12-96

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