[R-sig-ME] Estimated scale in R 2.8.1
Douglas Bates
bates at stat.wisc.edu
Tue Feb 10 14:55:51 CET 2009
A word of caution. There is a reason that the function sigma() is not
exported from the lme4 package, meaning that you must use
lme4:::sigma
to access it rather than the more obvious
sigma
Functions that are exported from the namespace of a package are
intended for general use. Functions that are not exported are
generally for internal use. Users who are sufficiently determined can
access them but doing so is on a "caveat emptor" basis.
I do not export this function because I'm not sure that this
calculation is appropriate for all generalized linear mixed models
(GLMMs). There are many areas where the definition of the likelihood
in a GLMM and its relationship to the iteratively reweighted least
squares (IRLS) algorithm, which for GLMMs becomes a penalized IRLS,
become murky, to me at least.
I wouldn't want to provide a measure of the appropriateness of a model
only to find out later that I had been misleading users.
On Tue, Feb 10, 2009 at 2:45 AM, Martin Henry H. Stevens
<HStevens at muohio.edu> wrote:
> have you tried
> lme4:::sigma(model)
> ?
> Hank
> On Feb 9, 2009, at 11:23 PM, Nola M. Stephens wrote:
>
>> Thanks for the suggestion. But when I try sigma(model), I get this error
>> message: could not find function "sigma". Any other thoughts?
>>
>> Thanks!
>> nola
>>
>> Ben Bolker wrote:
>>>
>>> Your mileage may vary, but I have found
>>>
>>> lme4:::sigma(model)
>>>
>>> to be a reasonably reliable way to get it.
>>>
>>> Ben Bolker
>>>
>>> Nola Stephens wrote:
>>>>
>>>> Hi,
>>>> When using earlier version of R (2.6.2), I got a scale factor for an
>>>> lmer model (where family=binomial). But after downloading R version
>>>> 2.8.1, I'm unable to find this value.
>>>>
>>>> I'd really appreciate some advice on how to find this.
>>>> Thanks!
>>>> nola
>>>>
>>>> _______________________________________________
>>>> R-sig-mixed-models at r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>
>>>
>>
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>
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