Hi, David. It sounds like you are talking about a zero-inflated model, e.g., a zero-inflated Poisson (ZIP) or zero-inflated negative binomial (ZINB). You could also fit a zero-inflated normal model (ZIN; Joe Schafer and a colleague wrote a paper about that model in the late 1990's; they called it a 'two-part model'). I never studied the ZIN model closely, but presumably the normal part of the model would allow negative predicted values, which I would not be happy with in your application.
You can fit a 2-level multilevel ZIP, ZIN, ZINB, etc in PROC NLMIXED and you can probably find related SAS code in the SAS-L archives; especially posts by Dale McLerran (sp?). HTH Steve ________________________________________ Message: 1 Date: Fri, 4 Sep 2009 14:25:33 -0400 From: David Judkins <[email protected]> Subject: [Impute] Robustness of Multi-Level Modeling Software To: "[email protected]" <[email protected]> Message-ID: <[email protected]> Content-Type: text/plain; charset="us-ascii" This is not an imputation question, but I don't know of a list serve for complex modeling questions. Maybe one of you will be able to help. Consider a mixed binary-normal distribution that results in a large point mass on the edge of an otherwise more-or-less normal distribution. An example is number of alcoholic drinks per day. Cigarettes per day is another example. Or the number of questions reading questions answered correctly on a sample that contains a large number of children who can't read at all. The child reading example is my real concern because the children come grouped by school. Anyone know of robustness studies of MLwin, HLM, Mixed, MPLUS, et cetera to this radical departure from normality? I have heard it asserted that school-level departures from normality are more of a concern than student-level departures, but is this too much of a departure? David Judkins Senior Statistician Westat 1650 Research Boulevard Rockville, MD 20850 (301) 315-5970 [email protected] From rlittle <@t> umich.edu Mon Sep 7 10:52:57 2009 From: rlittle <@t> umich.edu (Rod Little) Date: Mon Sep 7 10:53:02 2009 Subject: [Impute] RE: Impute Digest, Vol 47, Issue 1 In-Reply-To: <[email protected]> References: <[email protected]> <[email protected]> Message-ID: <pine.wnt.4.64.0909071150330.5...@sph-050164-bio.adsroot.itcs.umich.edu> David, the sequential regression program IVEware allows for "mixed" variable types like the one you describe. I think it multiply imputes using a two stage model, for presence/absence and then amount given presence. Rod On Mon, 7 Sep 2009, Gregorich, Steven wrote: > Hi, David. > > It sounds like you are talking about a zero-inflated model, e.g., a > zero-inflated Poisson (ZIP) or zero-inflated negative > binomial (ZINB). You could also fit a zero-inflated normal model (ZIN; Joe > Schafer and a colleague wrote a paper > about that model in the late 1990's; they called it a 'two-part model'). I > never studied the ZIN model closely, but > presumably the normal part of the model would allow negative predicted > values, which I would not be happy with > in your application. > > You can fit a 2-level multilevel ZIP, ZIN, ZINB, etc in PROC NLMIXED and you > can probably find related SAS > code in the SAS-L archives; especially posts by Dale McLerran (sp?). > > HTH > > Steve > ________________________________________ > > Message: 1 > Date: Fri, 4 Sep 2009 14:25:33 -0400 > From: David Judkins <[email protected]> > Subject: [Impute] Robustness of Multi-Level Modeling Software > To: "[email protected]" > <[email protected]> > Message-ID: > <[email protected]> > Content-Type: text/plain; charset="us-ascii" > > This is not an imputation question, but I don't know of a list serve for > complex modeling questions. Maybe one of you will be able to help. > > Consider a mixed binary-normal distribution that results in a large point > mass on the edge of an otherwise more-or-less normal distribution. An > example is number of alcoholic drinks per day. Cigarettes per day is another > example. Or the number of questions reading questions answered correctly on a > sample that contains a large number of children who can't read at all. The > child reading example is my real concern because the children come grouped by > school. > > Anyone know of robustness studies of MLwin, HLM, Mixed, MPLUS, et cetera to > this radical departure from normality? I have heard it asserted that > school-level departures from normality are more of a concern than > student-level departures, but is this too much of a departure? > > > David Judkins > Senior Statistician > Westat > 1650 Research Boulevard > Rockville, MD 20850 > (301) 315-5970 > [email protected] > _______________________________________________ > Impute mailing list > [email protected] > http://lists.utsouthwestern.edu/mailman/listinfo/impute > > > ___________________________________________________________________________________ Roderick Little Professor and Chair, Department of Biostatistics U-M School of Public Health Tel (734) 936 1003 M4208 SPH II Fax (734) 763 2215 1420 Washington Hgts email [email protected] Ann Arbor, MI 48109-2029 http://www.sph.umich.edu/~rlittle/
