Regression imputation works by using a regression equation derived from the observed data to predict the missing values. For instance, if we are missing a patient's blood pressure reading, we can use their age, weight, and other available health indicators to estimate the missing value. The process generally involves the following steps:
Identify the variables with missing values. Select predictor variables that are correlated with the missing variable. Develop a regression model using the predictor variables. Use the model to estimate and impute the missing values.
