Imputationbased
Imputation-based methods are statistical techniques used to handle missing data in datasets. Missing data can occur due to various reasons such as data entry errors, equipment malfunctions, or respondents refusing to answer certain questions. Imputation-based methods aim to fill in these missing values to ensure that the dataset is complete and can be analyzed without bias.
There are several types of imputation methods, each with its own advantages and limitations. Mean imputation
Regression imputation uses a regression model to predict the missing values based on other variables in the
Imputation-based methods are widely used in various fields such as healthcare, social sciences, and engineering. They