title: Using multiple imputation to deal with missing data and attrition in longitudinal studies with repeated measures of patient-reported outcomes.
abstract: OBJECTIVE
  Missing data is a ubiquitous problem in studies using patient-reported measures, decreasing sample sizes and causing possible bias. In longitudinal studies, special problems relate to attrition and death during follow-up. We describe a methodological approach for the use of multiple imputation (MI) to meet these challenges.
  
  
  METHODS
  In a cohort of patients treated with percutaneous coronary intervention followed with use of repetitive questionnaires and information from national registers over 3 years, only 417 out of 1,726 patients had complete data on all measure points and covariates. We suggest strategies for use of MI and different methods for dealing with death along with sensitivity analysis of deviations from the assumption of missing at random, all with the use of standard statistical software. The Mental Component Summary from Short Form 12-item survey was used as an example.
  
  
  CONCLUSIONS
  Ignoring missing data may cause bias of unknown size and direction in longitudinal studies. We have illustrated that MI is a feasible method to try to deal with bias due to missing data in longitudinal studies, including attrition and nonresponse, and should be considered in combination with analysis of sensitivity in longitudinal studies. How to handle dropout due to death is still open for debate.
authors: Danish Ramazzini Centre, Department of Occupational Medicine - University Research Clinic, Hospital West Jutland, Herning, Denmark.
authors: Karin
authors: K
authors: Biering
authors: WestChronic, Regional Hospital West Jutland, Herning, Denmark ; Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.
authors: Niels Henrik
authors: NH
authors: Hjollund
authors: Section of Biostatistics, Department of Public Health, Aarhus University, Aarhus, Denmark.
authors: Morten
authors: M
authors: Frydenberg
keywords: PCI; SF-12; nonparticipants; nonrespondents
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