regressioimputointi
Regressioimputointi, or regression imputation in English, is a statistical technique used to fill in missing data points in a dataset. It involves building a regression model based on the observed values of one or more variables to predict the missing values of another variable. For example, if a dataset has missing values for income, a regression model could be built using other variables like education level, age, and employment status to estimate the missing income figures.
The process typically involves selecting predictor variables that are known to be correlated with the variable