similar to: Help with write.foreign (exporting data to Stata)

As you know, Stata support in 'foreign' was frozen a while back at Stata version 12. R-core has received a request from a grad student to 'give top priority' to supporting Stata 13. That is not going to happen, not least because none of us has access to Stata. However, according to Stata's documentation both Stata 12 and 13 use format 115, so foreign::read.dta should be

Hi I recently imported data from r into Stata. I then ran the linear regression model I've been working on, only to discover that the results are somewhat (though not dramatically different). the standard errors vary more between the two programs than do the coefficients themselves. Any suggestions on what I've done that causes this mismatch? Thanks, Kate -- View this message in

I hope someone here knows the answer to this since it will save me from delving deep into documentation. Based on 22 pairs of vectors, I have noticed that tetrachoric correlation coefficients in stata are almost uniformly higher than those in R, sometimes dramatically so (TCC=.61 in stata, .51 in R; .51 in stata, .39 in R). Stata's estimate is higher than R's in 20 out of 22

Is anyone aware of an R procedure similar to STATA's "heckprob" procedure? "Heckprob" fits maximum likelihood probit models correcting for sample selection bias. Thanks, Richard Saba Department of Economics Auburn University Email: sabaric@auburn.edu [[alternative HTML version deleted]]

>On Wed, 3 Aug 2005, Bernd Weiss wrote: > >> I am trying to replicate some multilevel models with binary outcomes >> using R's "lmer" and "glmmPQL" and Stata's gllmm, respectively. > >That's not going to happen as they are not using the same criteria. the glmmPQL and lmer both use the PQL method to do it ,so can we get the same result by

Dear R users, I'm trying to specify a generalized linear mixed model in R, basically a Poisson model to describe monthly series of counts in different regions. My aim is to fit subject-specific curves, modelling a non-linear trend for each region through random effects for linear splines components (see Durban et al, Stat Med 2005, or " Semiparametric regression" by Ruppert et al,

Dear all, I am trying to replicate some multilevel models with binary outcomes using R's "lmer" and "glmmPQL" and Stata's gllmm, respectively. The data can be found at <http://www.uni-koeln.de/~ahf34/xerop.dta>. The relevant Stata output can be found at <http://www.uni- koeln.de/~ahf34/stataoutput.txt>. First, you will find the unconditional model,

Hi folks I am using the lmer function (in the lme4 library) to analyse some data where individuals are clustered into sets (using the SetID variable) with a single fixed effect (cc - 0 or 1). The lmer model and output is shown below. Whilst the fixed effects are consistent with stata (using xtmixed, see below), the std dev of the random effect for SetID is very very small (3.5803e-05)compared to

Hello, I am working with zero inflated models for a current project and I am getting wildly different results from R's zeroinfl(y ~ x, dist="negbin") command and Stata's zinb command. Does anyone know why this may be? I find it odd considering that zeroinfl(y ~ x, dist="poisson") gives identical to output to Stata's zip function. Thanks, --david [[alternative

I'm trying to replicate a time-series cross-sectional analysis (countries over years) with SEs clustered by country. ?The original analysis was done in Stata 10 with: xtreg [DV] [IVs] fe cluster(country). Using plm() in R (cran.r-project.org/web/packages/plm/index.html), I've replicated the coefficients. I sought to estimate country-clustered SEs with vcovHC(), and tried a variety of

Hi everyone, I am looking to do some manual maximum likelihood estimation in R. I have done a lot of work in Stata and so I have been using output comparisons to get a handle on what is happening. I estimated a simple linear model in R with lm() and also my own maximum likelihood program. I then compared the output with Stata. Two things jumped out at me. Firstly, in Stata my coefficient

foreign package does not support dataset saved at stata 13. anyone knows any wayt to make it works? [[alternative HTML version deleted]]

Hi, An R newbie here. I am using R 1.6 currently and have (successfully, I think) installed the Foreign package. Tried to import a data file created with Stata 7.0 SE. Had minor problems with syntax then R decided that my file was not really a Stata file. It rejected the file saying 'Not created by Stata 5-7/SE'. Any suggestions on how to convince R that this is really, truly a Stata

Full_Name: peter muhlberger Version: 2.7.1 OS: Ubuntu x86_64 dual core Submission from: (NULL) (70.238.206.13) I've spent half a day generating .dta files using write.dta only to have them crash my copy of Stata. I eventually discovered that removing a string variable with a maximum observed length of 280 characters allows Stata to read the file without problems. A Stata limit is that the

Long ago (Sat, 2 Nov 2002), Bill Hart <w.hart at sbcglobal.net> wrote: > An R newbie here. I am using R 1.6 currently and have > (successfully, I think) installed the Foreign package. > Tried to import a data file created with Stata 7.0 > SE. Had minor problems with syntax then R decided > that my file was not really a Stata file. It rejected > the file saying

Dear list, I am trying to replicate some Stata results but having a tough time doing it in R. The goal is to obtain a difference-in-difference estimate in a model with simple state fixed effects. The "state" variable is a factor, but some levels are missing. It appears that Stata automatically recognizes this and works around it. It also automatically pick "ME" as the base

Concerning this article, Christopher Zorn, "Generalized Estimating Equation Models for Correlated Data: A Review with Applications." 2001. American Journal of Political Science 45(April):470-90. The author very kindly provides data for replication on his web page: http://www.emory.edu/POLS/zorn/Data/GEE.zip. I've been comparing the Professor Zorn's results obtained with

Hi... In Stata, there is the ability to display scatter plots with data points at the same (x,y) location, using the 'jitter' command of the twoway scatter stata command. Anyone know of a way that I can do the equivalent thing in R? For non-Stata readers, if jitter is enabled in stata, and n-points would be at the same (x,y) location, the points are offset a bit (according to

R-helpers, I am hoping to find someone who uses both R and program Stata for GLMs. I am a beginner R user, finding my own way through; learning code etc. at the same time as learning the statistics I need to complete my project. What I have is the code from Stata and am trying to reproduce the same analysis in R - my program of choice. . glm count md ms rf sg, family(poisson)

Hello, I am switching to R from Stata and I am having particular trouble with the transition from Stata's 'xtabond' and 'ivreg' commands to the "plm" package. I am trying to replicate some of the dynamic panel data work using the UK Employment data in Arellano and Bond (1991) and available as 'EmplUK' under the 'plm' package. I have been