log(y1)-log(y2)= beta*(x+1 - x)
==>
log(y1/y2)=beta
==>
y1/y2=exp(beta)
it is odds .
@dode wrote:
I am doing linear regression when i check my outcome was not normally distributed so I transformed into log and it's worked. Now how I interpret the beta coefficient in log scal?
Is there a way to expandcit it back to interpretation would be easier ?
The response variable does not have to be normally distributed to use linear regression.
The residuals have to be normally distributed to use linear regression, and then the requirement to be normally distributed is used only when doing statistical testing; it is not used when fitting the model.
So it is possible you did not need to perform the log transformation at all.
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!
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.