04-30-2018 11:54 AM
I am running a regularized regression on several traits using the following code:
Proc glmselect data = DalReg1 plots(stepaxis=normb)=coefficients;
Model TW = Protein TGW SGD GL GW Size Shape / selection = LASSO(stop=none choose = cvex);
The output is great. However, I am wondering how to obtain standard errors for each coefficient. Help suggestions on this, please?
04-30-2018 12:01 PM - edited 04-30-2018 12:02 PM
The standard error for the coefficients appears in the parameter estimates results which should be in the output by default. Do mean to ask how to get that information into a data set?
04-30-2018 01:07 PM
Ballardw: Here is the output. There is no SE.
04-30-2018 04:42 PM
There are no SE provided when variable selection is performed with LASSO. There might be a good reason for that. Models resulting from variable selection methods do not account in their parameter estimates SE for model uncertainty. You can get parameter SEs for the chosen model, conditional on that choice, with other regression procedures, such as GLM, GENMOD or GLIMMIX.
04-30-2018 05:52 PM
Thanks PG. I agree. I thought there must be a good reason for not having SEs in LASSO procedure. I might have to do some more literature review on this. I chose LASSO because I have multicollinearity in my data but I am curious what SEs would be, if it is possible to generate them. Thanks again!
04-30-2018 02:53 PM
I am not sure if I am familiar with NLMIXED. Is there any other way with proc GLMSELECT? If not I might just to have a go at NLMIXED and see.
05-01-2018 07:09 AM
proc hpgenselect data=sashelp.class ;
model weight = sex height age/ CL ;
selection method=Lasso(choose=SBC) details=all;
You will see :
NOTE: The CL option is not available for the LASSO method. NOTE: The HPGENSELECT procedure is executing in single-machine mode. NOTE: * Optimal Value of Criterion NOTE: There were 19 observations read from the data set SASHELP.CLASS.
05-01-2018 05:32 PM
This is what I have seen:
NOTE: The CL option is not available for the LASSO method.
NOTE: The HPGENSELECT procedure is executing in single-machine mode.
NOTE: * Optimal Value of Criterion
NOTE: There were 1496 observations read from the data set WORK.DALREG1.
NOTE: PROCEDURE HPGENSELECT used (Total process time):
real time 1.07 seconds
cpu time 0.51 seconds
I just read about Bayesian LASSO that has the ability to generate SE. However, it requires a macro, an area I am, sadly, not competent with. Any help from anybody please?