[R-sig-ME] lme4 Question

Ben Bolker bbolker at gmail.com
Wed Dec 3 02:45:59 CET 2014

Hash: SHA1

  [forwarding to r-sig-mixed-models]

On 14-12-02 07:08 PM, Aimee Tallian wrote:
> Hello Ben,
> My name is Aimee Tallian and I am a Ph.D. student at Utah State
> University. I have a question about you package, 'lme4'.
> I have ran a bunch of analyses a while back in version 1.0-6, and
> have since updated to version 1.1-7. I have gone back to the
> initial analyses since I updated the package, and the results have
> changed. Everything is mostly the same except for the standard
> errors and p-values. What was significant is not anymore in several
> cases, even though the code and data are the exact same. See output
> below:
> *Output (lme4_1.0-6) *
> [image: Inline image 1]
> *Output (lme4_1.1-7) Same output in versions 1.1-6 / 1.1-5* [image:
> Inline image 2]
> This statement is the only real change associated with SE that I
> found between the versions that I have been using:
> *From the news for version 1.1-4*: Standard errors of fixed effects
> are now computed from the approximate Hessian by default (see the
> use.hessian argument in vcov.merMod); this gives better (correct)
> answers when the estimates of the random- and fixed-effect
> parameters are correlated (Github #47)
> I dug into the subject and it appears that this is the cause of my
> inflated SE and p-values. I tried: summary(a1fit1,
> use.hessian=FALSE), and as you suggested in the pdf manual, this
> returned my results from before.
> So, this is suggesting that my previous results are incorrect and
> that I should use the estimates from the newer version (which means
> a full start over)? Or is there justification for using my previous
> results and using the hessian = FALSE command? I.e., how do I know
> if my fixed and random effect parameters are correlated?
> I really appreciate any advice you might have on the subject!
> Thanks,
> Aimee

Version: GnuPG v1.4.11 (GNU/Linux)


More information about the R-sig-mixed-models mailing list