Re: [R] A question on glmnet analysis

(11/03/25 22:40), Nick Sabbe wrote: > 2. Which model, I mean lasso or elastic net, should be selected? and > why? Both models chose the same variables but different coefficient values. > You may want to read 'the elements of statistical learning' to find some > info on the advantages of ridge/lass

Re: [R] A question on glmnet analysis

(11/03/26 0:12), Mike Marchywka wrote: Would you post your data or if you did I missed it? Sorry, I did not. This is patients' data and I have to obtain some permission from my office to send it, so ... I don't have an answer for you but curious as I was interested in similar analyses with

Re: [R] A question on glmnet analysis

Hi Nick, Thanks a lot for your quick response. Sorry for delayed response becasue of time difference between us. (11/03/25 22:40), Nick Sabbe wrote: > > I haven't read all of your code, but at first read, it seems right. > > > > With regard to your questions: > > 1. Am I doing it correctly or not?

[R] A question on glmnet analysis

Hi, I am trying to do logistic regression for data of 104 patients, which have one outcome (yes or no) and 15 variables (9 categorical factors [yes or no] and 6 continuous variables). Number of yes outcome is 25. Twenty-five events and 15 variables mean events per variable is much less than 10. The

[R] Within factor & random factor

Hi, I am quite new to R and trying to analyze the following data. I have 28 controls and 25 patients. I measured X values of 4 different locations (A,B,C,D) in the brain image of each subject. And X ranges from 0 to 1. I think "control or patient" is a between subject factor and location is a wi