[R-sig-ME] lme4 and deviance

[Douglas Bates]

I share your concern about how to define the scaled deviance.  The trick,
as you say, is deciding what the saturated mixed model is.  I don't know of
a good way of defining it.

It might be best to just refer to the log-likelihood and not derive
anything called "deviance".

On Thu, May 21, 2015 at 9:09 AM Nadège Jacot <Nadege.Jacot at unige.ch> wrote:

> Dear list,
>
> I'm trying to understand why the deviance function returns -2 log
> likelihood in lme4 and not the "true" deviance as with lm().
>
> The scaled deviance is defined as the difference of -2 log likelihood
> between the model of interest and the saturated model but what is the
> saturated mixed model? For balanced data, some authors (e.g. Hoffman 2014,
> Longitudinal Analysis: Modeling Within-Person Fluctuation and Change)
> define the saturated mixed model as a model with saturated means (one fixed
> effect for each time point) and unstructured variance but such a model is
> not available for unbalanced data.
>
> And if we can compute the scaled deviance, what is the deviance?
>
> Thanks in advance for any hint.
>
> Nadège Jacot
>
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