[R-sig-ME] lmer with binomial distribution of random effects
thierry.onkelinx at inbo.be
Mon Mar 9 09:22:48 CET 2015
I would take a step back first. Do you have enough data to fit such a
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
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
2015-03-09 2:15 GMT+01:00 Ben Bolker <bbolker op gmail.com>:
> El Kihal, Siham <Siham.ElKihal op ...> writes:
> > Dear lmer() friends,
> > I am trying to estimate a model with a random
> > intercept, and 2 random slopes.
> > I believe that my betas (slopes) do not follow
> >a normal distribution, but rather a bimodal distribution.
> > The reason for this that there are two possible
> > mechanisms that influence the evolution of this variable,
> > one with a negative influence and another one with a
> > positive influence. This is why I need to use a bimodal
> > distribution for my slopes to avoid the fact that
> > both effects right now cancel out.
> > Does anyone of you has already done this or has
> > an idea how to concretely implement this using lmer()?
> This sounds like a latent mixture model problem. lme4 doesn't
> do this; you *might* be able to implement an expectation-maximization
> wrapper around lme4 that would do it, but it wouldn't be entirely
> trivial. If I had to do this I would probably turn to JAGS/BUGS.
> Looking forward to other answers from the list ...
> R-sig-mixed-models op r-project.org mailing list
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