On Fri, Feb 20, 2009 at 4:19 AM, Bernardo Rangel Tura
<t...@centroin.com.br> wrote:
> Hi R-masters
>
> I need yours help about a problema in one of may ongoing researchers.
>
> In my research the subjects (20 in total) answer 60 questions (20 type
> G, 20 type S and 20 type P).
>
> Which questions is classified about 3 factor (2 level each) and the
> subject score with 2 scale (not integer value is possible but rare): Val
> range -7 to 7 and other Car range 1 to 7.
>
> This a code to fake database of research
>
> Subj<-rep(1:20,each=60)
> Sti<-rep(c("G","S","P"),40)
> SP<-rep(c("S","P"),60)
> AG<-rep(c("A","P"),60)
> Mer<-rep(c("M","NM"),60)
> Car<-round(runif(120,1,7),0)
> Val<-round(runif(120,-7,7),0)
> base<-data.frame(Subj,Sti,SP,AG,Mer,Car,Val)
>
> In my hypothesis:
>
> logit(Sti=="G") ~ SP+AG+Mer+Car+Val+SP*Car+Mer*Val+AG*Val + errorG
>
> logit(Sti=="S") ~ SP+AG+Mer+Car+Val+SP*Car+Mer*Val+AG*Val + errorS
>
> logit(Sti=="P") ~ SP+AG+Mer+Car+Val+SP*Car+Mer*Val+AG*Val + errorP
>
> I test and the 3 terms of error (errorG,errorS,errorP) is correlated.
>
> So I think useful adjust a system of logistic equations to tread the 3
> equations and in same time to obtain estimatives of effects and
> uncorrelated error terms.
>
>
> The systemfit package fit linear system and non-linear system but is
> possible adjust a logistic system in R?
>No, but I think this is a very interesting question. If you just had 3 dichotomous outputs, I think you could estimate this model with lmer in the lme4 package. "Stack" the 3 sets of data together, include dummy variables for the different questions, and then introduce correlated random errors that affect the 3 groups. lmer can estimate correlated cariance structures. That might work, but after reading you question over a few times, I think first of all you have to reconsider idea about your output variable. I've not seen anybody take a 3 category output and treat it as a sequence of dichotomies in this way. Rather, we'd either need to treat this as an ordered output or an unordered one. If it is ordered, then I do not know of an R estimator that will help. As luck would have it, I was recently reading about a Stata package produced by sociologist R Williams (Notre Dame). He offers a package for ordinal model (he calls them ordinal generalized linear models, but AFAICT that may be a misnomer because the probability model underlying the ordinal logistic does not fall within the exponential family that is usually used to define the GLM). Nevertheless, he offers the code for Stata http://www.nd.edu/~rwilliam/oglm/ . Since I'm not a Stata user, I've not tried it. It seems like a good exercise for one of us to get a graduate student programmer to find out how he estimates those models and make an R package. I believe with 3 or more unordered categories in the output, you have a multinomial problem, not just the simpler problem of 3 logistic models sharing some errors. I suppose if these choices were sequenced, it could be represented as a conditional logistic regression as well. (Example, is the subject sick or not? If sick, is it cancer or heart disease?) There is an R package for fitting to heteroskedastic multinomial choice models. Fellow political scientist Walter Mebane (Cornell) and Jasjeet S. Sekhon published an article on this model and they put their R package on CRAN "multinomRob" Robust Estimation of Overdispersed Multinomial Regression Models. Oh, well, good luck with your project. I hope we'll get some lively answers :). If you get private answers, please forward me the useful ones. PJ > Thanks in advance > > > > -- > Bernardo Rangel Tura, M.D,MPH,Ph.D > National Institute of Cardiology > Brazil > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Paul E. Johnson Professor, Political Science 1541 Lilac Lane, Room 504 University of Kansas ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
