RE: st: RE: Poisson regression with score/scale as DV

[Reinhardt Jan Dietrich <jan.reinhardt@paranet.ch>]

Although dichomotimisation could become the name of a new method ;-)

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: Dienstag, 3. April 2012 11:49
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: RE: Poisson regression with score/scale as DV

I do know how to spell "dichotomise"...

On Tue, Apr 3, 2012 at 10:34 AM, Nick Cox <njcoxstata@gmail.com> wrote:
> Jan and I are not bound to agree. I don't agree with the argument that
> it's clearly OK to count yes-no answers to different questions but
> clearly not OK to add graded answers to different questions.
>
> Scores will never satisfy measurement purists, but the job of the data
> analyst is to squeeze the juice out of never-ideal data, not to
> pontificate about perfect oranges that would yield perfect juice.
>
> In this case, one obvious difficulty is whether (e.g.) my "Often" is
> equivalent to anybody else's, let alone everybody else's, but
> dichomotimising the scale would not remove that difficulty.
>
> It's unclear whether piling up just refers to skewness or you have
> zero inflation too.
>
>
> On Tue, Apr 3, 2012 at 10:09 AM, Clinton Thompson
> <clintonjthompson@gmail.com> wrote:
>> Many thanks for the replies, Jan & Nick.  As for the suggestion to
>> create a sum index based on the dichotomization of the ordinal
>> variables, I must admit that I'm unsure of how/why this would be
>> superior to the current index.  In my situation, the score follows
>> from the summing of nine composite questions about the frequency with
>> which a person engages in an activity where each composite question
>> has four responses ("Never", "Rarely", "Sometimes", "Often").  The
>> corresponding values for the responses are [0,3].  Maybe I don't yet
>> understand the intricacies of the Poisson distribution but re-scaling
>> the component questions from [0,3] to [0,1] will just re-scale the
>> score variable from [0,27] to [0,9], which still leaves me w/ a
>> bounded DV with a pile-up of responses at zero.  Either way (and if I
>> understand both of you), it sounds like Poisson is a reasonable way to
>> model this variable/response?
>>
>> Nick -- I hadn't considered -glm, f(binomial)- but I'll look further
>> into it.  (And thanks for correcting my reference to Austin Nichols'
>> presentation.  My spelling implied his last name is Nichol -- not
>> Nichols.  Embarrassing mistake.)
>>
>> Thanks again,
>> Clint
>>
>>
>> On Tue, Apr 3, 2012 at 10:43 AM, Nick Cox <njcoxstata@gmail.com> wrote:
>>> Lots of social scientists agree with you, while lots of other social
>>> and other scientists spend most of the time doing precisely that.
>>>
>>> On Tue, Apr 3, 2012 at 9:07 AM, Reinhardt Jan Dietrich
>>> <jan.reinhardt@paranet.ch> wrote:
>>>
>>> ... Ordinal items should definitely not be summed up ...

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