A review of the reporting and handling of missing data in cohort studies with repeated assessment of exposure measures
Open Access
- 11 July 2012
- journal article
- review article
- Published by Springer Science and Business Media LLC in BMC Medical Research Methodology
- Vol. 12 (1), 96
- https://doi.org/10.1186/1471-2288-12-96
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.Keywords
This publication has 114 references indexed in Scilit:
- Multiple imputation by chained equations: what is it and how does it work?International Journal of Methods in Psychiatric Research, 2011
- Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical exampleJournal of Clinical Epidemiology, 2010
- Periodontitis and incidence of cerebrovascular disease in menAnnals of Neurology, 2009
- Childbearing is associated with higher incidence of the metabolic syndrome among women of reproductive age controlling for measurements before pregnancy: the CARDIA studyAmerican Journal of Obstetrics and Gynecology, 2009
- Effects of Changes in Depressive Symptoms and Cognitive Functioning on Physical Disability in Home Care EldersThe Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 2009
- Homogeneity in the relationship of serum cholesterol to coronary deaths across different cultures: 40-year follow-up of the Seven Countries StudyEuropean Journal of Preventive Cardiology, 2008
- Recreational amphetamine use and risk of HIV-related non-Hodgkin lymphomaCancer Causes & Control, 2008
- Periodontal disease, tooth loss, and cancer risk in male health professionals: a prospective cohort studyThe Lancet Oncology, 2008
- Changes in serum calcium, phosphate, and PTH and the risk of death in incident dialysis patients: A longitudinal studyKidney International, 2006
- Life-course body size and perimenopausal mammographic parenchymal patterns in the MRC 1946 British birth cohortBritish Journal of Cancer, 2003