[R-sig-ME] Deviance residuals don't sum up to deviance

[Steve Walker]

Does this document by Ben Bolker clear it up?

https://github.com/lme4/lme4/blob/master/misc/notes/deviance.rmd

Steve

On 2014-08-22, 9:07 AM, Roelof Coster wrote:
> Thanks for the suggestion!
>
> I can use the example which you suggest:
>
>> gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
> data = cbpp, family = binomial)
>> deviance(gm1)
> [1] 184.0531
>> sum(residuals(gm1, type= "deviance")^2)
> [1] 73.47428
>
> So here is what I don't understand: these deviance residuals, squared,
> don't add up to the total deviance as I expected they would.
>
> Best regards, Roelof Coster
>
>
>
>
> 2014-08-22 13:58 GMT+02:00 Martin Maechler <maechler at stat.math.ethz.ch>:
>
>>
>>> Hello,
>>> I fitted a logistic regression model with glmer. In the resulting model,
>>> the reported deviance is not the same as the sum of the squares of the
>>> residual deviances. The deviance is 3909, the sum of square deviance
>>> residuals is 3747.
>>
>>> These two should be equal, shouldn't they? The difference seems too large
>>> for a roundoff error, I think.
>>
>>> My data are 150k observations and the fitted probabilities are generally
>>> very small (between 1e-7 and 1e-2, median 1e-4).
>>
>> Can you at least show the exact R function calls that you did to
>> produce it?  Even better,
>> can you please use the 'gm1' from the first example in
>> help(glmer),
>>
>>    (gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
>>                  data = cbpp, family = binomial))
>>
>> and now show how you compute these to sums with *reproducible* R
>> code.  That way we (the readers of R-SIG-ME) can be motivated
>> much more to help you.
>>
>>
>>> Thanks! Roelof Coster
>>
>> You are welcome ;-)
>> Martin Maechler
>>
>
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