- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content
Hi,
I know you can do a partial F-test with PROC REG to jointly test a set of parameters. For example,
PROC REG DATA = dataset
MODEL y = x1 x2 x3;
TEST x2=x3=0;
RUN;
Which gives me output that looks like this.
I would like to know if there is a way to perform the same the test using PROC GLM.
Thank you very much.
Sincerely,
Bill
- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content
Google finds the answer quickly.
https://communities.sas.com/t5/Statistical-Procedures/Proc-GLM-How-to-do-partial-F-test/td-p/108159
Paige Miller
- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content
- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content
I think it is the answer.
Paige Miller
- Mark as New
- Bookmark
- Subscribe
- Mute
- RSS Feed
- Permalink
- Report Inappropriate Content
I'm not sure how the solution below provides an answer on how to write a PROC GLM step that would jointly test a set of parameters using a partial f-test.
------------------------------------------------------
Y = B0 + B1*Asian + B2*Black + B3*White + B4*X + B5*X*Asian + B6*X*Black + B7*X*White + e
The CLASS RACE statement creates dummy variables (Asian, Black, White) with values (1,0,0) for RACE="Asian", (0,1,0) for RACE="Black" and (0,0,1) for RACE="White". SAS will force parameters B3 and B7 to zero because they are redundant, so that the linear equations are:
Asian : Y = (B0+B1) + (B4+B5)*X
Black : Y = (B0+B2) + (B4+B6)*X
White : Y = B0 + B4*X
The F test for effect RACE*X tests the hypothesis B5=B6=B7=0 which, if true, would mean that all slopes are equal.
hth
PG
Message was edited by: PG corrected typo reported by Steve Denham.