Missing Data A Systematic Review of How They Are Reported and Handled

Iris Eekhout*, Michiel R. de Boer, Jos W. R. Twisk, Henrica C. W. de Vet, Martijn W. Heymans

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

147 Citations (Scopus)

Abstract

Background: The objectives of this systematic review are to examine how researchers report missing data in questionnaires and to provide an overview of current methods for dealing with missing data.

Methods: We included 262 studies published in 2010 in 3 leading epidemiologic journals. Information was extracted on how missing data were reported, types of missing, and methods for dealing with missing data.

Results: Seventy-eight percent of the studies lacked clear information about the measurement instruments. Missing data in multi-item instruments were not handled differently from other missing data. Complete-case analysis was most frequently reported (81% of the studies), and the selectivity of missing data was seldom examined.

Conclusions: Although there are specific methods for handling missing data in item scores and in total scores of multi-item instruments, these are seldom applied. Researchers mainly use complete-case analysis for both types of missing, which may seriously bias the study results.

Original languageEnglish
Pages (from-to)729-732
Number of pages4
JournalEpidemiology
Volume23
Issue number5
DOIs
Publication statusPublished - Sept-2012

Keywords

  • ITEM SCORES
  • MULTIPLE IMPUTATION
  • QUESTIONNAIRE DATA
  • GUIDELINES

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