search for: moleps2

Dear all, I was intrigued by the ctree command and wanted to check it out. I first ran the demo with example(ctree) and did get the survival graphs in the end. Upon doing this with my own data and yielding a "Invalid operation on a survival time" I tried to rerun example(ctree) and now I also get "Invalid operation on a survival time" after the example runs plot(GBSG2ct)...

Dear all, I just received a file from a colleague in spss. The read.spss could not finish the file due to an error (Unrecognized record type 7, subtype 18 encountered in system file) so instead I converted the file using stat-transfer. Looking at my data I see that most labels are in the attributes and I?d love to access them and assign the pertinent variables to factors without doing the whole

Dear R?ers I?m trying to get a summary table using latex and summary in the rms package to no avail. I?m running R 2.10.1, Mac OS X snow leopard and I have the mactex 2009 distribution installed. Any obvious things I?m missing? //M options(digits=3) set.seed(173) sex <- factor(sample(c("m","f"), 500, rep=TRUE)) age <- rnorm(500, 50, 5) treatment <-

Dear R´ers, How can I create one single factor variable from two variables incorporating all possible combinations of the values?? test<-sample(c("A",NA,"B"),100,replace=T) test2<-sample(c("E",F,"A"),100,replace=T) tes<-cbind(test,test2) pseduocode: r<-function(test,test2) r AE AF AA NAE NAF NAA BE BF BA //M [[alternative HTML

Dear listers, Does anyone have any experience running marginal structural models in r or can point me in the direction of any good tutorials on this? Regards, //M

Dear all, I?m having trouble getting a list of regression variables back into a dataframe. mydf <- data.frame(x1=rnorm(100), x2=rnorm(100), x3=rnorm(100)) mydf$fac<-factor(sample((0:2),replace=T,100)) mydf$y<- mydf$x1+0.01+mydf$x2*3-mydf$x3*19+rnorm(100) dlply(mydf,.(fac),function(df) lm(y~x1+x2+x3,data=df))->dl here I?d like to use ldply(dl,coef(summary)) or something

Dear all, I?m specifying the fisher.exact test for use with summary.formula as follows: u<-function(a,b){ j<-fisher.test(a) p<-list(P=j$p.value,stat=NA,df=NA,testname=j$method,statname="") return(p) } However I?m also required to specify stat & df. However this doesnt apply to the fisher test. I?ve tried specifying them as NA and "" without

Dear all, Given rr<-data.frame(r1<-rnorm(1000,10,5),r2<-rnorm(1000,220,5)) How can I add a column (rr$p) for the joint probability of each r1 & r2 pair? I know how to add the column.. I just dont know how to compute the p value for joint probabilities given the two samples. //M

Dear All, I?ve been trying to find an option to scatter3D from rcmdr to remove the individual points from the plots but to no help so far. Removing the residuals is easy, but I cannot find a similar point option. Is there such an option that can be set to FALSE? Best, //M

Dear all, Using the SetInternet2(TRUE) option works wonders with R in my sealed down work-environment. However, I'd like to use RCurl and apparently the proxy settings are not carried over. Is it possible to figure out the proxy-IP and port number from R after invoking SetInternet2? //M

Dear all, I?m trying to get a output table for age and the summary of a and b, stratified by epo as follows using summary.formula h<-data.frame(a=sample(c("A",NA),100,replace=T),b=sample(c("B",NA),100,replace=T),age=rnorm(100,50,25),epo=sample(c("Y","N"),100,T)) library(rms)

Dear all, With the latest update of Hmisc I no longer have any problems with latex. However using the ctable option produces latex code that at least on both the miktex distribution at work and mactex distribution at home refuses to run due to an extra blank line inserted between the multicolumn lines in the latex code... It runs fine if the line is deleted or if the ctable option is left out.

Dear R?ers. I?ve got a dataset with age and year of diagnosis. In order to age-standardize the incidence I need to transform the data into a matrix with age-groups (divided in 5 or 10 years) along one axis and year divided into 5 years along the other axis. Each cell should contain the number of cases for that age group and for that period. I.e. My data format now is ID-age (to one

I?m trying to run a logistic joinpoint regression utilising the ljr package. I?ve been using the forward selection technique to get the number of knots for the analysis, but I?m uncertain as to my results and the interpretation. The documentation is rather brief ( in the package and the stats in medicine article is quite technical) and without any good examples. At the moment I?m thinking 1)find

glm(A~B+C+D+E+F,family = binomial(link = "logit"),data=tre,na.action=na.omit) Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : contrasts can be applied only to factors with 2 or more levels however, glm(A~B+C+D+E,family = binomial(link = "logit"),data=tre,na.action=na.omit) runs fine glm(A~B+C+D+F,family = binomial(link =

Dear all, Is there an implementation of Simon & Makuch method of plotting the survival function with time-dependent variables. I?m only able to find event.chart in Hmisc for the purpose and I would prefer the Simon and Makuch method. I believe stata has it implemented for this purpose, but I cannot find it on CRAN. Simon R, Makuch RW. A non-parametric graphical representation of the

Dear R´ers.. In this mock dataset how can I generate a logical variable based on whether just tes or tes3 are NA in each row?? test<-sample(c("A",NA,"B"),100,replace=T) test2<-sample(c("A",NA,"B"),100,replace=T) test3<-sample(c("A",NA,"B"),100,replace=T) tes<-cbind(test,test2,test3)

Dear all, I did post this more or less identical mail in a follow up to another question I posted, but under another heading. I try again, but now under the correct header. upon running this code (from the Hmisc library-latex function) I believe the call to summary.formula is allright and produces wonderful tables, but the latex command results in a correct formatted table but where all the