Jean-Baptiste The most immediate difference I see is that you use a logit link in the R code but a probit link function in the stata code. Joe
On Fri, Jan 22, 2010 at 8:25 AM, Jean-Baptiste Combes <jbcom...@laposte.net>wrote: > Hello people, > > I am in the process of migrating from Stata to R and I would like to check > if my results are similar under the two softwares: > > Here is my GLM command under R > nurse.model<-glm(pQSfteHT~dQSvacrateHTQuali3_2 + dQSvacrateHTQuali3_3 + > dQSvacrateHTQuali3_4 + dQSvacrateHTQuali3_5 + cluster_32 + cluster_33 + > cluster_34 ,family=binomial(link = "logit")) > > > and below the stata command > glm pQSfteHT dQSvacrateHTQuali3_2 dQSvacrateHTQuali3_3 dQSvacrateHTQuali3_4 > dQSvacrateHTQuali3_5 cluster_32 cluster_33 cluster_34, link(probit) > family(binomial) robust > > Apart from the robust option, it seems to me from what I understand that I > should get the same things. > Stata output: > > > > *Second model (N=690* > > > > *Coef.* > > *p-value* > > Constant** > > 0.241*** > > 0.000 > > QV>SV>0 > > 0.076*** > > 0.001 > > SV>QV>0 > > 0.071** > > 0.027 > > QV>SV=0 > > 0.051** > > 0.019 > > SV>QV=0 > > 0.042 > > 0.368 > > Mental Health HTs > > -0.226*** > > 0.000 > > Acute Teaching HTs > > 0.159*** > > 0.000 > > Other HTs > > 0.084 > > 0.200 > > > R output (Sorry for the presentation, but I am not able at the moment to > produce nice tables, the variables are in the same order as above) > Call: > glm(formula = pQSfteHT ~ dQSvacrateHTQuali3_2 + dQSvacrateHTQuali3_3 + > dQSvacrateHTQuali3_4 + dQSvacrateHTQuali3_5 + cluster_32 + > cluster_33 + cluster_34, family = binomial(link = "logit")) > > Deviance Residuals: > Min 1Q Median 3Q Max > -2.297e+00 2.107e-08 2.107e-08 6.275e-06 3.850e-01 > > Coefficients: > Estimate Std. Error z value Pr(>|z|) > (Intercept) 4.476e+01 1.950e+04 0.002 0.998 > dQSvacrateHTQuali3_2 -1.112e+00 2.136e+04 -5.21e-05 1.000 > dQSvacrateHTQuali3_3 -5.365e-01 2.576e+04 -2.08e-05 1.000 > dQSvacrateHTQuali3_4 -2.011e+01 1.693e+04 -0.001 0.999 > dQSvacrateHTQuali3_5 -6.509e-01 4.040e+04 -1.61e-05 1.000 > cluster_32 -3.194e-01 1.788e+04 -1.79e-05 1.000 > cluster_33 -2.857e-02 2.475e+04 -1.15e-06 1.000 > cluster_34 -2.209e+01 9.666e+03 -0.002 0.998 > > (Dispersion parameter for binomial family taken to be 1) > > Null deviance: 15.0690 on 688 degrees of freedom > Residual deviance: 7.2049 on 681 degrees of freedom > AIC: 23.205 > > Number of Fisher Scoring iterations: 24 > > > > My suggestion is that I have something wrong with my data under R (I am > confident with the Stata results). What do you think? I am not expecting > you > to solve my problem as I reckon it is a bit difficult for you as you do not > know the data, I just would like an opinion on the differences found > between > the two softwares, do you agree that there is something wrong? > > Thank you for reading this e-mail. > > I would like to thank you in advance and alos the people who answered my > previous e-mail that was very kind of you. > > Jean-Baptiste > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > -- Joseph C. Magagnoli Doctoral Student Department of Political Science University of North Texas 1155 Union Circle #305340 Denton, Texas 76203-5017 Email: jcm0...@unt.edu [[alternative HTML version deleted]] ______________________________________________ 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.
