Dropping irrelevant variables from a regression equation might provide a better regression in what sense?
A) Only when the irrelevant variables are uncorrelated with the treatment(s).
B) Might facilitate more efficient/precise estimates of the treatment effect (smaller standard errors).
C) Only if the irrelevant variables have low p-values.
D) Only if the irrelevant variables have many outliers.

Question

Quizplus · Accepted Answer

Dropping irrelevant variables from a regression equation can help in obtaining more efficient and precise estimates of the treatment effect by reducing the standard errors of the coefficients. This can facilitate better interpretation and understanding of the relationship between the predictor and response variables. However, dropping variables that are correlated with the treatment or have a low p-value can also improve the regression. Outliers do not necessarily impact the relevance of variables and therefore dropping irrelevant variables cannot be justified by the presence of outliers.

Dropping Irrelevant Variables from a Regression Equation Might Provide a Better