In epidemiological studies, missing data can arise due to various reasons such as non-response, lost to follow-up, or data entry errors. Missing data can introduce bias and reduce the statistical power of a study. Mean imputation helps in retaining the sample size and minimizing potential biases, thereby enhancing the reliability and validity of the epidemiological findings.
