https://blogs.sas.com/content/iml/2017/01/09/ods-output-any-statistic.html
See the examples above with the instructions on how to save statistics and output.
@kwa wrote:
Dear community members,
I am using PROC REG with the REG= option to obtain a ridge regression. I have done the following;
Plotted the ridge estimates against λ.
Chosen λ for which the coefficient estimates are not rapidly changing and have sensible signs.
I know this method has no specific objective basis and is heavily criticised by others.
However my question is as follows, how can I get the p values, t values and standard errors for my selected choice of λ ? I seem only to get the regression coefficients which are different from the ridge regression that was un tuned for λ.
Any help will be greatly appreciated
Best ,
Ka
We can’t see your code so at this point probably not. Please post your code.
The instructions on in the l8nk have enough information to show you how to obtain the values. Include what you’ve tried so far as well.
You can use the OUTSEB option to get the standard errors for the RIDGE estimates in the outest= data set:. However, I don't think the estimates follow a t distribution, so you don't get test statistics or p-values. If you want p-values, I think you will need to bootstrap.
The estimates are biased, so it's not clear to me that the p-values will be useful.
proc reg outest=est ridge=0.02 outseb;
model Y=x1 x2 x3 ;
run;
proc print data=est(where=(_TYPE_ contains "RIDGE"));
run;
You can use the OUTSEB option to get the standard errors for the RIDGE estimates in the outest= data set:. However, I don't think the estimates follow a t distribution, so you don't get test statistics or p-values. If you want p-values, I think you will need to bootstrap.
The estimates are biased, so it's not clear to me that the p-values will be useful.
proc reg outest=est ridge=0.02 outseb;
model Y=x1 x2 x3 ;
run;
proc print data=est(where=(_TYPE_ contains "RIDGE"));
run;
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!
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.