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 language | English |
|---|---|
| Pages (from-to) | 729-732 |
| Number of pages | 4 |
| Journal | Epidemiology |
| Volume | 23 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Sept-2012 |
Keywords
- ITEM SCORES
- MULTIPLE IMPUTATION
- QUESTIONNAIRE DATA
- GUIDELINES