Which approach would replace missing values based on using an equation such as the following: Missing Value = 10.0 + (2.5 * VAR1) + (1.8 * VAR2) + (3.0 * VAR3)?

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Quizplus · Accepted Answer

The approach described is regression imputation, which involves using a regression equation to estimate missing values based on the relationships between the missing variable and other variables in the dataset. This approach is appropriate when there is a strong relationship between the missing variable and other variables, as indicated by the high regression coefficients in the equation. Mean substitution and conditional mean substitution are simpler methods that may be appropriate when there are only a few missing values or when the missing values are not strongly related to other variables in the dataset. Regression imputation with error is a more complex approach that accounts for the variability in the imputed values, but it may not be necessary in cases where the missing values are relatively few and the imputation equation is well-specified.

Which Approach Would Replace Missing Values Based on Using an Equation