Different model result with log-transformed vs. original dependent variable in linear mixed model

Asked Jan 15 '19 at 22:56

Active Jan 15 '19 at 22:56

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I fit my data with linear mix model using y and log-transformed y like below:

fit1 = lmer(y~Visit+Treatment+(1|Subject.ID))
fit2 = lmer(log(y)~Visit+Treatment+(1|Subject.ID))

Treatment effect in fit1 is not significant, but it is significant in fit2 (with log(y) ).

I'm confused about how should I interpret the model result.

Can anyone explain what is the correct way to interpret mixed model result when dependent variable is log-transformed vs not log-transformed.

Thanks a lot in advance!

asked Jan 15 '19 at 22:56

zesla

2

This has come up before. One example here and another here. – dimitriy Jan 15 '19 at 23:02
Here is another possible duplicate. Also, it would be a good idea to check that the residuals are normally distributed. – Robert Long Jan 16 '19 at 11:22

0 Answers0