A healthcare executive is using regression to predict total revenues.She is deciding whether or not to include both patient length of stay and insurance type in her model.Her first regression model only included patient length of stay.The resulting r²was .83, with an adjusted r²of .82 and her level of significance was .003.In the second model, she included both patient length of stay and insurance type.The r²was .84 and the adjusted r²was .80 for the second model and the level of significance did not change.Which of the following statements is true? A)The second model is a better model. B)The first model is a better model. C)The r² increased when additional variables were added because these variables significantly contribute to the prediction of total revenues. D)The adjusted r²always increases when additional variables are added to the model.

Question

Quizplus · Accepted Answer

The first model is better because although the r-squared (r^2) increased slightly in the second model, the adjusted r-squared decreased, indicating that the addition of insurance type did not improve the model enough to justify the added complexity. The adjusted r-squared is a more reliable measure when comparing models with a different number of predictors because it adjusts for the number of predictors in the model.

A Healthcare Executive Is Using Regression to Predict Total Revenues