Question about random effects
There is another kind of power issue involved as well: Keeping spurious variance components in the model leads to significant loss in statistical power. Stroup (2012, Generalized linear mixed models: Modern concepts, methods and applications, p. 185): "Neither the [maximal] nor the [minimal] linear mixed models are appropriate for most repeated measures analysis. Using the [maximal] model is generally wasteful and costly in terms of statistical power for testing hypotheses. On the other hand, the [minimal] model fails to account for nontrivial correlation among repeated measurements. This results in inflated [T]ype I error rates when non-negligible correlation does in fact exist. We can usually find middle ground, a covariance model that adequately accounts for correlation but is more parsimonious than the [maximal] model. Doing so allows us full control over [T]ype I error rates without needlessly sacrificing power." See also: http://arxiv.org/abs/1511.01864
On Mon, May 23, 2016 at 5:57 PM, Ben Bolker <bbolker at gmail.com> wrote:
I agree, although I'll also say that if you are faced with a power
imbalance (reviewer/supervisor/etc. insists that it should be removed),
in the case where the random effect variance is estimated as zero there
is really very little (no?) *practical* difference in this case between
keeping or removing the random effect. In particular, the estimates of
any other variance components in the model, as well as all of the
contents of summary() [point estimates and Wald standard errors of
fixed-effect of coefficients] should be identical (try it and see).
cheers
Ben Bolker
On 16-05-23 11:42 AM, Thierry Onkelinx wrote:
If the random effect reflects the design of the study then it should
remain
in the model. ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and
Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to
say
what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey 2016-05-23 17:13 GMT+02:00 Adriana Maldonado Chaparro < maldonado.aa at gmail.com>:
Greetings, I want to ask for advise on the following issue: I fitted a mixed model where I'm trying to explain variation in Litter
Sex
Ratio as a function of social network position. In this model the random effect, individual identity, explained none of the variance, and one of
the
reviewers argued that I should exclude it from my model because of these reason. I think I should keep it because I have repeated measures. What
are
your thoughts on this matter?
Thanks in advance,
Adriana Maldonado
Postdoctoral Researcher
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