Web Reference: Feb 1, 2024 · Here we aim to explain in a non-technical manner key issues and concepts around missing data in biomedical research, and some common methods for handling missing data. 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. If only one variable has missing entries, life is easy. But what if all the predictor variables have a little bit of missingness (with some observations having multiple entries missing)?
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