04-11-2015 09:13 AM
I am trying to do a linear regression to computer whether body weight can predict blood pressure after controlling for age, healthstatus, and physical activity. Here, my DV (blood pressure) is continuous and my IV(body weight) is continuous. Also, I have several covariate IVs; age is continous, healthstatus is categorical (dummy coded 1-5), and physical activity is continous (# hours doing physical activity). To do this, should I use proc glm or proc reg?
04-11-2015 07:53 PM
I recommend proc glm. There you can use the class statement to dummy code the categorical variables.
You can use also proc reg, but then first you need to pre-process your data (creating dummy variables "manually").
04-13-2015 08:06 AM
You can use STEPWISE BACKWISW ... option of MODEL to get rid of multicollinearity and get the best model .
04-13-2015 10:10 AM
"Best models" with categorical variables are messy, and those methods in PROC REG really won't help. The categorical dummy variables are by definition collinear.
I would approach this with PROC GLM or MIXED, and look at the chapter on Analysis of Covariance in SAS for Mixed Models, 2nd ed.