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Missing data: the impact of what is not there.
- Source :
-
European journal of endocrinology [Eur J Endocrinol] 2020 Oct; Vol. 183 (4), pp. E7-E9. - Publication Year :
- 2020
-
Abstract
- 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.
- Subjects :
- Age of Onset
Aged
Aged, 80 and over
Asymptomatic Diseases
Hormone Replacement Therapy
Humans
Hypothyroidism drug therapy
Hypothyroidism epidemiology
Logistic Models
Odds Ratio
Outcome Assessment, Health Care
Placebos
Randomized Controlled Trials as Topic standards
Randomized Controlled Trials as Topic statistics & numerical data
Sample Size
Thyroxine therapeutic use
Bias
Reproducibility of Results
Research Design standards
Subjects
Details
- Language :
- English
- ISSN :
- 1479-683X
- Volume :
- 183
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- European journal of endocrinology
- Publication Type :
- Academic Journal
- Accession number :
- 32688333
- Full Text :
- https://doi.org/10.1530/EJE-20-0732