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From |
Adam Olszewski <adam.olszewski@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: logistic regression with clustered SE vs. xtlogit |

Date |
Wed, 19 Jun 2013 01:31:16 -0400 |

Hi Tim, Thank you very much for the explanation and the links which led to even more reading and my better understanding of the models. The random-effects logistic model with dummies for survey questions (extending to Rasch model) works well except for problems with stability with different number of integration points (as assessed by -quadchk-) - which as I understand may be due to highly correlated nature of the data.. Best, AO On Wed, Jun 19, 2013 at 1:09 AM, Adam Olszewski <adam.olszewski@gmail.com> wrote: > Hi Tim, > Thank you very much for the explanation and the links which led to even more > reading and my better understanding of the models. > The random-effects logistic model with dummies for survey questions > (extending to Rasch model) works well except for problems with stability > with different number of integration points (as assessed by -quadchk-) - > which as I understand may be due to highly correlated nature of the data.. > Best, > AO > > > On Mon, Jun 17, 2013 at 10:08 PM, Timothy Mak <tshmak@hku.hk> wrote: >> >> Hi Adam, >> >> This sounds like an Item Response Theory problem to me. >> http://en.wikipedia.org/wiki/Item_response_theory >> >> However, usually they assume an underlying continuous score rather than an >> underlying binary factor. If you definitely want a binary underlying factor, >> then the model to consider is a latent class model. >> >> If you want to assume an underlying continuous score, then the Rasch model >> may be appropriate. Your random-effects logistic model can be thought of as >> a very simplistic Rasch model - i.e. it assumes all questions have the same >> probability of being 0 or 1. See >> http://www.stata.com/support/faqs/statistics/rasch-model/ for a very useful >> discussion of the Rasch model and how to do it in Stata. >> >> The clustered SE approach is the same as doing -xtlogit, pa- with the >> corr(independent) and vce(robust) option. The difference between -xtlogit, >> re- and -xtlogit, pa- is explained in >> http://www.stata.com/support/faqs/statistics/random-effects-versus-population-averaged/ >> >> I wouldn't recommend using -xtlogit, pa-, since (a) it's not commonly (if >> ever) used for this kind of analysis, and (b) it's inefficient even if it's >> appropriate. >> >> That's my twopence... >> >> Tim >> >> >> >> -----Original Message----- >> From: owner-statalist@hsphsun2.harvard.edu >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Adam Olszewski >> Sent: 16 June 2013 08:13 >> To: statalist@hsphsun2.harvard.edu >> Subject: st: logistic regression with clustered SE vs. xtlogit >> >> Dear listers, >> I have a dataset with results from a 15-item questionnaire, with a >> binary response to each question (the questions are felt to measure >> the same underlying binary factor). I want to study the correlation of >> demographic variables (age, gender) on whether the answer is 0 or 1. >> The questions are obviously correlated between the 15 items filled out >> by the same person. >> After reading about different models, it seems that logistic >> regression with clustered standard errors (-logit varlist, vce(cluster >> ID)-) or random-effects logistic model (-xtset ID-, then: -xtlogit >> varlist, re-) might be appropriate, and give similar, although not >> identical results. I am not sure what is the conceptual difference >> between them. Would one be preferred over the other in some >> circumstances? Or did I even pick wrong tools for the problem? I >> thought about regressing the mean of answers, but such a dependent >> variable does not meet assumption for any model that I know of. >> Sorry if this sounds basic, but I rarely wander beyond routine >> logistic regression and I am a little puzzled by xtlogit. >> Best regards, >> Adam Olszewski >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/faqs/resources/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/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: logistic regression with clustered SE vs. xtlogit***From:*Adam Olszewski <adam.olszewski@gmail.com>

**st: RE: logistic regression with clustered SE vs. xtlogit***From:*Timothy Mak <tshmak@hku.hk>

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