A review of hot deck imputation for survey non-response discusses the method of replacing missing data with values from similar units. Despite its widespread use, the theoretical foundation is less developed than other imputation methods. The paper reviews various hot deck approaches, their statistical properties, and applications, including the U.S. Census Bureau's use in the Current Population Survey (CPS) and the National Health and Nutrition Examination Survey (NHANES III). It highlights the importance of selecting appropriate donor pools and metrics for matching, and discusses the impact of sampling weights and multivariate missing data. The paper also addresses variance estimation and multiple imputation methods, emphasizing the need for careful consideration of assumptions and the potential for bias. It concludes with suggestions for future research, noting the limitations of hot deck imputation in complex scenarios and the importance of balancing precision and bias. The review underscores the role of hot deck imputation in survey data analysis, while acknowledging its challenges in ensuring accurate and reliable estimates.A review of hot deck imputation for survey non-response discusses the method of replacing missing data with values from similar units. Despite its widespread use, the theoretical foundation is less developed than other imputation methods. The paper reviews various hot deck approaches, their statistical properties, and applications, including the U.S. Census Bureau's use in the Current Population Survey (CPS) and the National Health and Nutrition Examination Survey (NHANES III). It highlights the importance of selecting appropriate donor pools and metrics for matching, and discusses the impact of sampling weights and multivariate missing data. The paper also addresses variance estimation and multiple imputation methods, emphasizing the need for careful consideration of assumptions and the potential for bias. It concludes with suggestions for future research, noting the limitations of hot deck imputation in complex scenarios and the importance of balancing precision and bias. The review underscores the role of hot deck imputation in survey data analysis, while acknowledging its challenges in ensuring accurate and reliable estimates.