Dealing with missing outcome data in randomized trials and observational studies.
By Rolf H. H. Groenwold, A. Donders, K. Roes, Frank E. Harrell, Karel G. M. Moons. American Journal of Epidemiology, 2012
391 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/07aa04eb03b4eac6832028138d4c0b5641b659cf
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
- Gary S. Collins
- Karel G. M. Moons
- Douglas G. Altman
- Joris A. H. de Groot
- Kristin L. Sainani
- S. Dutton
- A. Tajar
- Johannes B Reitsma
Citations in the corpus
- External validation of multivariable prediction models: a systematic review of methodological conduct and reporting (2014, background): “The majority (64%) of studies were assumed to have conducted complete-case analyses to handle missing values, despite methodological guidance to do the contrary [40-44].”
- Dealing With Missing Data (2015, methodology): “Complete-case analysis will also produce unbiased results for MAR data if one adjusts the analysis for all the covariates that predict missing data [1].”