Statistical Procedures

Programming the statistical procedures from SAS
BookmarkSubscribeRSS Feed
☑ This topic is solved. Need further help from the community? Please sign in and ask a new question.
CL52
Calcite | Level 5

Dear all,

I struggled to figure out how to derive SD and confidence interval for difference between groups in percentage change from baseline, analyzed in log-transformation. 

 

In proc mixed, I have [log(Post) - log(BL)] as response. and treatment as indepent variables, visit, and treatment by visit interaction. So I know, the coefficient beta1 for treatment (and beta0 as intercept), I can transform back to get the percentage change (exp(beta0+beta1) - 1)*100%. 

 

However what I am interested in is the difference between the group. 

[exp(beta0+beta1)-1] - [exp(beta0)-1] = exp(beta0)*(exp(beta1) - 1)

 

How can I derive the SD and CI of the above with the LSmeans output? 

Any reference I can go to? 

 

Many thanks!

Carrie 

 

 

1 ACCEPTED SOLUTION

Accepted Solutions
StatDave
SAS Super FREQ

The LSMEANS statement cannot be used to estimate or test nonlinear combinations of model parameters. For that, you can use the NLEST macro.

View solution in original post

1 REPLY 1
StatDave
SAS Super FREQ

The LSMEANS statement cannot be used to estimate or test nonlinear combinations of model parameters. For that, you can use the NLEST macro.

sas-innovate-white.png

Our biggest data and AI event of the year.

Don’t miss the livestream kicking off May 7. It’s free. It’s easy. And it’s the best seat in the house.

Join us virtually with our complimentary SAS Innovate Digital Pass. Watch live or on-demand in multiple languages, with translations available to help you get the most out of every session.

 

Register now!

What is ANOVA?

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.

Discussion stats
  • 1 reply
  • 1149 views
  • 2 likes
  • 2 in conversation