O'Reilly logo

Statistics for Health Care Management and Administration by David A. Rosenthal, John F. Kros

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Chapter 13Extensions of Multiple Regression

Chapter 12 provided an introduction to multiple regression, and this chapter continues that discussion. In particular, we consider the use and effect of dummy variables in multiple regression, the selection of best models in multiple regression, correlation among independent variables and the effect of this correlation, and the assessment of nonlinear relationships.

13.1 Dummy Variables in Multiple Regression

Chapter 11 discussed the correspondence between regression and the t test. That chapter also showed that the results of both analyses were essentially the same when a dummy variable alone was employed as the predictor variable in regression. This section examines the inclusion of a dummy variable, along with other continuous variables in multiple regression analysis, to produce what is sometimes called analysis of covariance (ANCOVA).

A Dummy Variable with No Interaction

Suppose we examine again the data shown in Figure 11.3. Those data show 20 hospital stays and the total charge for each. But this time we will include a second variable: sex of the patient. The length of stay and charges data were taken from actual hospital ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required