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From |
Clinton Thompson <clintonjthompson@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Poisson regression with score/scale as DV |

Date |
Tue, 3 Apr 2012 11:09:35 +0200 |

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 ... > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: RE: Poisson regression with score/scale as DV***From:*David Hoaglin <dchoaglin@gmail.com>

**Re: st: RE: Poisson regression with score/scale as DV***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**st: Poisson regression with score/scale as DV***From:*Clinton Thompson <clintonjthompson@gmail.com>

**st: RE: Poisson regression with score/scale as DV***From:*Reinhardt Jan Dietrich <jan.reinhardt@paranet.ch>

**Re: st: RE: Poisson regression with score/scale as DV***From:*Nick Cox <njcoxstata@gmail.com>

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