[R-sig-ME] Significance and lmer

[Ben Bolker]

Adam D. I. Kramer <adik at ...> writes:

> 
> Dear colleagues,
> 
> Please consider this series of commands:
> 
> a <- lmer(log(stddiff+.1539) ~ pred + m*v + option + (option|studyID),
> data=r1, subset=option>1, REML=FALSE)
> 
> b <- update(a, . ~ . - pred)
> 
> anova(a,b)
> 
> ...am I mistaken in thinking that the latter command will produce a test of
> whether "pred" is a significant predictor of log(stddiff+.1539)? I am
> concerned because of the results:
> 

  [snip]

> ...a significant result completely unrelated to the t-value. My
> interpretation of this would be that we have no good evidence that the
> estimate for 'pred' is nonzero, but including pred in the model improves
> prediction.

  It is possible for Wald tests (as provided by summary()) to 
disagree radically with likelihood ratio tests (look up "Hauck-Donner
effects", but my guess is that's not what's going
on here (it definitely can apply in binomial models, don't think
it should apply to LMMs but ?).

  I have seen some wonky stuff happen with update() [sorry, can't
provide any reproducible details], I would definitely try fitting
b by spelling out the full model rather than using update() and
see if that makes a difference.

  Other than that, nothing springs to mind.

  (Where does the log(x+0.1539) transformation come from???)