Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

Find a Community

- Home
- /
- Analytics
- /
- Data Mining
- /
- Limitations of SAS Enterprise Miner's variable sel...

- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Highlight
- Email to a Friend
- Report Inappropriate Content

04-26-2017 08:13 PM

Hi everyone,

I was just wondering, does SAS enteprise Miner's stepwise selection methods (Stepwise, Forward, Backward) take collinearity in the model into account? Or does one have to separately handle collinearity first before using the stepwise selection methods?

Thanks,

Paul

Accepted Solutions

Solution

05-02-2017
01:09 PM

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Highlight
- Email to a Friend
- Report Inappropriate Content

05-02-2017 12:59 PM

This post from my colleague a few years ago might help:

Also, the HP Regression node now outputs a Variance Inflation Factor table when you do a linear regression. The VIF measures how much the variance of a coefficient is increased due to collinearity. A VIF value of 1 indicates that there is no collinearity. Large values, for example 10 or more, indicate that collinearity might be a significant issue in the model.

All Replies

Solution

05-02-2017
01:09 PM

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Highlight
- Email to a Friend
- Report Inappropriate Content

05-02-2017 12:59 PM

This post from my colleague a few years ago might help:

Also, the HP Regression node now outputs a Variance Inflation Factor table when you do a linear regression. The VIF measures how much the variance of a coefficient is increased due to collinearity. A VIF value of 1 indicates that there is no collinearity. Large values, for example 10 or more, indicate that collinearity might be a significant issue in the model.

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Highlight
- Email to a Friend
- Report Inappropriate Content

05-02-2017 01:09 PM

Hi Wendy,

Thanks for the answer and article..

Paul

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Highlight
- Email to a Friend
- Report Inappropriate Content

05-02-2017 01:03 PM - edited 05-02-2017 01:05 PM

frupaul wrote:

Hi everyone,

I was just wondering, does SAS enteprise Miner's stepwise selection methods (Stepwise, Forward, Backward) take collinearity in the model into account? Or does one have to separately handle collinearity first before using the stepwise selection methods?

Thanks,

Paul

You could use Partial Least Squares regression, which is less sensitive to collinearity than Stepwise/Forward/Backward methods (which also have other drawbacks). With PLS, the issue of variable selection goes away (you use all variables) and you get coefficient estimates and predicted values which have lower mean square error than ordinary least squares regression methods, as shown in http://amstat.tandfonline.com/doi/abs/10.1080/00401706.1993.10485033