[R-sig-ME] mixed model with non-continuous numeric response

Reinhold Kliegl reinhold.kliegl at gmail.com
Mon Dec 22 15:04:19 CET 2008

See Venables and Ripley (2002, p.200) for an example modeling
three-levels of satisfaction (low, medium, high) as a surrogate
Poisson model. They also provide the technical justification. The
alternative is to fit it as multinomial model--not sure how, if it at
all, this can be done with glmer in its current implementation.

Reinhold Kliegl

On Mon, Dec 22, 2008 at 1:41 PM, Daniel Ezra Johnson
<danielezrajohnson at gmail.com> wrote:
> I don't think this is count data, is it???
> On Mon, Dec 22, 2008 at 12:40 PM, Reinhold Kliegl
> <reinhold.kliegl at gmail.com> wrote:
>> ( ...,  family="poisson")  is the most used option for count data
>> Reinhold Kliegl
>> On Mon, Dec 22, 2008 at 12:54 PM, Daniel Ezra Johnson
>> <danielezrajohnson at gmail.com> wrote:
>>> Dear all,
>>> I have survey results where the response is 1, 2, 3, or 4. These can
>>> be thought of as equally-spaced points on a scale, I don't have a
>>> problem with that. (They're actually more like "not at all", "some",
>>> "mostly", "totally"; the subject is judging a stimulus.)
>>> I want to model crossed random effects for Subject and Item. Am I way
>>> off base in modeling this data with a lmer(family="gaussian") model? I
>>> know it's not perfect, but is it really bad? If so, what could I do
>>> instead? (The error certainly wouldn't be binomial, right?)
>>> Thanks,
>>> Daniel
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