Missing Data Summary Tool
Summarize aggregate missing counts for one variable and take away an audit checklist.
Your entries stay in this page’s memory and are not submitted to us. Downloads are generated locally. Reloading or leaving the page clears your entries. Do not enter patient information.
Summarize one variable at one time point using aggregate counts. Define who was expected to have a measurement; do not count “not applicable” records as missing without considering the study definition.
Missingness summary
15.0% missing
18 missing and 102 observed out of 120 expected measurements.
No percentage alone establishes that missingness is harmless or determines whether imputation is appropriate.
What to investigate next
- Repeat this summary by study group and time point where appropriate.
- Record reasons for missingness without replacing unknown reasons with guesses.
- Assess assumptions with your team; this tool cannot identify MCAR, MAR, or MNAR.
- Missing counts across variables cannot be added to infer the number of incomplete participants.