BookmarkSubscribeRSS Feed
gpreece
Calcite | Level 5

Hello SAS Community!

 

I need to hear your thoughts regarding the best regression choice for my model.

 

Sample size is 15K

 

I have a dependent variable comprised of 12 items - all yes or no. The score can be between 0-12 all assigned equal values.

Further, my model consists of 17 predictor/independent variables. Variable range from gender (binary), income (categorical), to risk aversion scale (interval).

 

I initially planned to run an OLS Regression but I am getting conflicting opinions on whether or not that is the right option. Your opinions and advice is greatly appreciated.

 

 

Thanks,

Gloria 

1 REPLY 1
PaigeMiller
Diamond | Level 26

You will have problems with OLS since your independent variables are almost definitely correlated with one another.

 

Partial Least Squares regression will provide better model fits (lower mean square error of the coefficients, lower means square error of the predicted values) than OLS in this case, and will handle the collinearity between the predictors better than OLS will handle it.

--
Paige Miller

SAS Innovate 2025: Call for Content

Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!

Submit your idea!

What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 1196 views
  • 0 likes
  • 2 in conversation