[R] question on lasso

oslo hokut1 at yahoo.com
Sat Nov 5 22:22:20 CET 2016

Hi Dr. Franggakis;
This can be explained because of collinearity and suppressor variable in multiple regression models. In the first scenario, you have both correlated variables and suppressor variables in the second scenario you do not have this problem. I do wonder why to do not use the scale elastic net for this particular problem.
Good luck,Oslo 

    On Saturday, November 5, 2016 4:29 PM, Constantine Frangakis <cfranga1 at jhu.edu> wrote:

 I would appreciate any comments to the following question.
I am trying to build a model for survival based on 155 patients and 70 covariates using lasso. Lasso picks, three variables only, say X1,X2,X3, and  omits the others. I wanted to check why a particular (clinically important) variable, say X4, is omitted by lasso. One of the things I did was I ran lasso on X1,X2,X3 and X4 only. The results (coefs) I get are different from running all 70 variables, and in fact now X4 is not omitted.
Why is that ? should it not be that the global (among all 70 variables) optimum, which is X1,X2,X3 and not X4, be also the local (among the four only) optimum ?
Thank you for your consideration

Constantine Frangakis, PhD
Departments of Biostatistics
Psychiatry, and Radiology
Johns Hopkins University

    [[alternative HTML version deleted]]

R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

	[[alternative HTML version deleted]]

More information about the R-help mailing list