Open AccessMissing data: the impact of what is not there
Author(s) -
Rolf H. H. Groenwold,
Olaf M. Dekkers
Publication year - 2020
Publication title -
european journal of endocrinology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.897
H-Index - 148
eISSN - 1479-683X
pISSN - 0804-4643
DOI - 10.1530/eje-20-0732
Subject(s) - missing data , confounding , statistics , outcome (game theory) , medicine , econometrics , mathematics , mathematical economics
The validity of clinical research is potentially threatened by missing data. Any variable measured in a study can have missing values, including the exposure, the outcome, and confounders. When missing values are ignored in the analysis, only those subjects with complete records will be included in the analysis. This may lead to biased results and loss of power. We explain why missing data may lead to bias and discuss a commonly used classification of missing data.
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