[R-sig-ME] testing fixed effects in binomial lmer...again?

David Duffy David.Duffy at qimr.edu.au
Tue Jan 8 23:12:42 CET 2008

On Tue, 8 Jan 2008, Dimitris Rizopoulos wrote:
>> On Jan 8, 2008 5:38 AM, Achaz von Hardenberg <fauna at pngp.it> wrote:
>>> However, I am not sure about what I should do to test for the
>>> significance of fixed effects in the binomial case
> What about Bootstrap (parametric or not)? Would it be useful in this
> case?

The only problem is specifying a bootstrap mechanism that respects the
structure of the random effects.  So for time series data, your bootstrap
samples have to remain AR1 or whatever (ie you don't want gaps appearing that
aren't in the observed data), and for genetic type data (the kind I have),
that pseudosample people are appropriately related to one another.  Resampling
clusters works for that kind of data, though I think you need many clusters.
There are several papers in the area of genetic linkage analysis that have 
validated bootstrapping for a test that a variance component is zero.

But for testing simple hypotheses about particular fixed effects, 
a permutation/randomization test should work, I think.

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

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