Significance and lmer
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