[R-sig-ME] Significance and lmer

[Adam D. I. Kramer]

The problem turned out to be, indeed, differing numbers of observations.
This is likely due to me relying too much on update() to work as I
expected...it did not drop the observations previously dropped. The help
page for update makes it very clear that it just re-evaluates an altered
call, so this is my fault. Ben's comment about update() being wonky should
have given me a hint.

Preselecting cases using complete.cases() for both models brought the t
values and chi-square values much closer together--when t=.51 for the
coefficient, the chisq of a likelihood test for removing the variable from
the model was chisq=.25, leading to a reasonable p=.62.

Thanks very much to you and Ben Bolker!

--Adam

On Sun, 28 Mar 2010, David Duffy wrote:

> On Sat, 27 Mar 2010, Adam D. I. Kramer wrote:
>> On Sat, 27 Mar 2010, Ben Bolker wrote:
>> 
>>>> ...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.
>>> 
>>
>>>  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.
>> 
>> This produces no difference in b's estimates or the anova() statistics.
>> (That said, I originally was fitting [implicitly] with REML=TRUE, which did
>> make a difference, but not a big one).
>
> The two models both have the same number of observations, one hopes?  How 
> many observations per studyID and how many studyIDs?
>
>> Well, thanks for the reply. Are you, then, of the opinion that the above
>> interpretation is reasonable?
>
> I would be a bit nervous.  My interpretation would be that the model is 
> inappropriate for the data (as the Wald and LR tests should roughly agree for 
> a LMM, as Ben pointed out), and would look at diagnostic plots of residuals 
> etc.  The bunch of zeroes you mention may still be stuffing things up ;)  Is 
> a left-censored model plausible?
>
> Just my 2c, David Duffy.
>
> -- 
> | David Duffy (MBBS PhD)                                         ,-_|\
> | email: davidD at qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
> | Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
> | 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v
>