How to back-transform LSMEAN standard errors from PROC MIXED?

[ErikCB]

Hello- I noted the excellent exchange of info. back in 2012 on how to obtain accurate estimates of LSMEANS and standard errors using PROC GLIMMIX when the response variable has been log-transformed. Steve- thanks for the suggestion. However, I tried this approach but found no improvement in my residuals (non-constant variance problem). In a nutshell, here is my conceptual linear model:

ln (x...a continuous resp.variable) = f (y, z)...where y is continuous and z is a 3-level class variable. So the GLIMMIX program statement with the "fix" for back-transforming the LSMEANS would be:

PROC GLIMMIX DATA=example plots=all ;
CLASS z;
MODEL x= y  z/SOLUTION LINK=LOG;
LSMEANS z/CL DIFF ILINK;
RUN;

The resulting residuals display no improvement and are essentially the same as the output from a non-transformed model without the link=log statement. I am doubtless making a stupid mistake! I would appreciate any help you can offer. Thanks.

[bioepi]

Hi,

I'm working with a survey dataset of skewed fasting glucose level, when logn (fgl) transformed it is normally distributed. I need to use PROC MIXED. How can I back transform the LSMEANS and its standard error for the log-transformed data?

Thanks in advance.

[SteveDenham]

Please read all of the above, and consider using PROC GLIMMIX instead.

Steve Denham