Dear Thomas, Where you also able to replicate the second example? (the exaample that I turned the housing data into numerical variables) That is the one that my estimates differ.
Jean, On Wed, 10 Nov 2004, Thomas Lumley wrote: > On Wed, 10 Nov 2004, Jean Eid wrote: > > > Dear All, > > I have been struggling to understand why for the housing data in MASS > > library R and stata give coef. estimates that are really different. I also > > tried to come up with many many examples myself (see below, of course I > > did not have the set.seed command included) and all of my > > `random' examples seem to give verry similar output. For the housing data, > > I have changed the data into numeric vectors instead of factors/ordered > > factors. I did so to try and get the same results as in STATA and to have > > the housing example as close as possible to the one I constructed. > > > > I run a debian sid, kernel 2.4, R 2.0.0, and STATA version 8.2, MASS > > version 7.2-8. > > > > > > here's the example ( I assume that you have STATA installed and can run in > > batch mode, if not the output is also given below) > > > > That example shows the same results with Stata and polr() from MASS. > > For the housing data, I also get the same coefficients in Stata as with > polr(): > > In R: > library(MASS) > library(foreign) > write.dta(housing, file="housing.dta") > house.probit<-polr(Sat ~ Infl + Type + Cont, data = housing, weights = > Freq, method = "probit") > summary(house.probit) > ------------------------- > Re-fitting to get Hessian > > Call: > polr(formula = Sat ~ Infl + Type + Cont, data = housing, weights = Freq, > method = "probit") > > Coefficients: > Value Std. Error t value > InflMedium 0.3464233 0.06413706 5.401297 > InflHigh 0.7829149 0.07642620 10.244063 > TypeApartment -0.3475372 0.07229093 -4.807480 > TypeAtrium -0.2178874 0.09476607 -2.299213 > TypeTerrace -0.6641737 0.09180004 -7.235005 > ContHigh 0.2223862 0.05812267 3.826153 > > Intercepts: > Value Std. Error t value > Low|Medium -0.2998 0.0762 -3.9371 > Medium|High 0.4267 0.0764 5.5850 > > Residual Deviance: 3479.689 > AIC: 3495.689 > ------------------------ > > > In Stata > ----------------- > . use housing.dta > . xi: oprobit Sat i.Infl i.Type i.Cont [fw=Freq] > i.Infl _IInfl_1-3 (naturally coded; _IInfl_1 omitted) > i.Type _IType_1-4 (naturally coded; _IType_1 omitted) > i.Cont _ICont_1-2 (naturally coded; _ICont_1 omitted) > > Iteration 0: log likelihood = -1824.4388 > Iteration 1: log likelihood = -1739.9254 > Iteration 2: log likelihood = -1739.8444 > > Ordered probit estimates Number of obs = 1681 > LR chi2(6) = 169.19 > Prob > chi2 = 0.0000 > Log likelihood = -1739.8444 Pseudo R2 = 0.0464 > > ------------------------------------------------------------------------------ > Sat | Coef. Std. Err. z P>|z| [95% Conf. > Interval] > -------------+---------------------------------------------------------------- > _IInfl_2 | .3464228 .064137 5.40 0.000 .2207165 > .472129 > _IInfl_3 | .7829146 .076426 10.24 0.000 .6331224 > .9327069 > _IType_2 | -.3475367 .0722908 -4.81 0.000 -.4892241 > -.2058493 > _IType_3 | -.2178875 .094766 -2.30 0.021 -.4036254 > -.0321497 > _IType_4 | -.6641735 .0917999 -7.24 0.000 -.844098 > -.484249 > _ICont_2 | .2223858 .0581226 3.83 0.000 .1084676 > .336304 > -------------+---------------------------------------------------------------- > _cut1 | -.2998279 .0761537 (Ancillary parameters) > _cut2 | .4267208 .0764043 > ------------------------------------------------------------------------------ > > > > -thomas > ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
