similar to: R question for Stata users

Hi, everyone: I ask for help about translating a stata program into R. The program perform cross validation as it stated. #1. Randomly divide the data set into 10 sets of equal size, ensuring equal numbers of events in each set #2. Fit the model leaving out the 1st set #3. Apply the fitted model in (2) to the 1st set to obtain the predicted probability of a prostate cancer diagnosis. #4. Repeat

I have a table statement that returns the following: [10.839,10.841] (10.841,10.843] (10.843,10.846] (10.846,10.848] (10.848,10.85] 0 0 0 0 1 (10.85,10.852] (10.852,10.854] (10.854,10.857] (10.857,10.859] (10.859,10.861] 0 0 0 0 0 What I want to do is get the upper bound

Hi R Users, I have a dataframe like this: id x rho A 1 0.1 B 20 0.5 C 2 0.9 ... I want to do a scatter plot of "x" versus "rho" but for each point on the scatter plot I want the corresponding entry for "id" instead of points. In STATA I can do so by twoway (scatter x rho, mlabel(id)) How can I do the same in R? I am sure there is some simple way to do

Dear colleagues, I have a question regarding controlling the jitter when plotting predictions in the rms package. Below I've simulated some data that reflect what I'm working with. The model predicts a continuous variable with an ordinal score, a two-level group, and a continuous covariate. Of primary interest is a plot of the group by score interaction, where the score is the ordinal

Hi... I'm working through the book, A Handbook of Statistical Analyses using R by Everitt, and I'm trying to do the following (p. 19 of his book): boxplot(log(marketvalue)~country, data = subset(Forbes2000, country %in% c("United Kingdom","Germany","India","Turkey")), ylab="log(marketvalue",

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

I have a client who uses Stata 11. Can anyone advise me on ways of transferring data from this version of Stata to R? Reading the documentation for read.dta in package foreign it seems it only allows for versions up to Stata 10. I don't know Stata at all but a bit of poking around on their website led me to believe Stata 11 couldn't write in Stata 10 format. However Stata 11 can

Hi I am using Stata 10 and I need to import a data set in stata 10 to R, I have saved the dataset in lower versions of Stata as well by using saveold command in Stata. My RAM is 4gb and the stata file is 600MB, I am getting an error message which says : "Error: cannot allocate vector of size 3.4 Mb In addition: There were 50 or more warnings (use warnings() to see the first 50)" Thus

Hi, I have a new job, and everyone here uses Stata. I won't give up on R, but I must learn better how to exchange data between the two softwares. I am now focusing on importing data from Stata to R, and I must confess that I am a bit disappointed with the read.dta function from the foreign package because IT typically happens that (i) I get a big R file (for example, a 15Mb Stata file

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 R-list, I am currently working on a dataset with a colleague who uses stata. We fit a random intercept model to the data (decisions clustered in participants) and get closely the same results in stata (using xtreg re) and R (using the lme4 or multilevel package). Now in stata, there is an additional option for the regression to control for clustering; the vce(cluster clustvar) option,

OK...newbie question here. Either I'm reading the docs wrong, or I'm totally confused. Given the following: x<-c("aaa","bbb","ccc") y<-rep(0,3) z<-rep(0,3) is.character(x) [1] TRUE is.numeric(y) [1] TRUE Now...I want to create a data frame, but keep the data types. In reading the docs, I assume you do it this way:

I am evaluating a switch from Stata to R. I don't need to extensive Statistical methods, but the main reason I am exploring the switch is the coding flexibility in R (e.g. Stata does not support linear/quadratic programming). I have been going over the R syntax and I had a quick question: In Stata, one has a very useful construction called "by", e.g. by month signal: gen xxx =

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

Hello I would like to develop the use of R. Trying R and more particulary the cox model, I am surprised by discrepancies between results with stata and R for a cox model With the same data base, I get a hazard ratio (4.82) that is not the same obtained with stata (4.52) You will find attached the file leukemia.dta I used (Stata) Here are the codes for R library(foreign)

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

Hello, I'm not a Stata user so I'm trying to reproduce Stata results that are given to me in R. I would like to use a GLM with a complementary log-log function. The stata code I have is: glm c IndA fia, family(binomial s) link(cloglog) offset(offset) The R code is: glmt <- glm(data=dataset, c ~ IndA + fia, offset = offset, family = binomial(link = cloglog)) Which yields

Hi... I'm trying to understand the following syntax: cor.test(~mortality + hardness,data=water,method="pearson") which is the same as: cor.test(water$mortality,water$hardness,data=water,method="pearson") Can anyone point me to the correct doc or explain to me how to interpret "~mortality + hardness"? Thanks, Joe

Hello In STATA there is command which has regression with clustering option. Can anyone tell me what is the command for the same in R for example in STATA its regress Height Weight, cluster(id) Thanks in Advance Regards Sunita -- View this message in context: http://www.nabble.com/Regression---cluster-option-in-STATA-tp25241948p25241948.html Sent from the R help mailing list archive at

Dear Colleagues I have been fitting some multinomial logistic regression models using R (version 1.6.1 on a linux box) and Stata 7. Although the vast majority of the parameter estimates and standard errors I get from R are the same as those from Stata (given rounding errors and so on), there are a few estimates for the same model which are quite different. I would be most grateful if