Korean Journal of Anesthesiology· 2013· Review
The prevention and handling of the missing data
- 1,759citations
- 2013year
Short summary
This review outlines methods to prevent and handle missing data, which can reduce statistical power and bias study estimates, leading to invalid conclusions.
AI-generated from the title and abstract; the full text is not read.
Key points
- Missing data is prevalent even in well-designed studies.
- Missing data can lead to reduced statistical power and biased estimates.
- The manuscript covers types, mechanisms, and handling techniques for missing data.
- Recommendations are provided for managing missing data.
AI-generated from the title and abstract; the full text is not read.
Abstract
Even in a well-designed and controlled study, missing data occurs in almost all research. Missing data can reduce the statistical power of a study and can produce biased estimates, leading to invalid conclusions. This manuscript reviews the problems and types of missing data, along with the techniques for handling missing data. The mechanisms by which missing data occurs are illustrated, and the methods for handling the missing data are discussed. The paper concludes with recommendations for the handling of missing data.
The authors' abstract, as published at the source. Korean Journal of Anesthesiology, 2013 · DOI ↗
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Field: Statistics and Probability
Statistics and ProbabilityMathematics