search for: rasanga

...uot;,"fpr") plot(perf,ave="threshold",spread.estimate="boxplot") But I want know whether we could get this for more than one marker, so we can look at how good the markers in combination to predict the infection. I'm very grateful for any suggestion/help.   Thanks Rasanga   [[alternative HTML version deleted]]

...Cutoff=sens@x.values[[1]][num.cutoff], Sensitivity=sens@y.values[[1]][num.cutoff], Specificity=spec@y.values [[1]][num.cutoff])) }   se.sp(cutoff=0.5, pred)   I would be grateful if someone could let me know how to get 95% CIs for these sensitivity and specificity?   Thanks vermuchch in advance. Rasanga       [[alternative HTML version deleted]]

Dear R List, I want to download kinship_1.2_S.tar.gz in http://mayoresearch.mayo.edu/mayo/research/biostat/splusfunctions.cfm to R. Once save this file to C:\, how I could load into R? I am working in Windows XP. Usually what I do is, I go to "packages" and then "install packages from local zip files". This procedure fails for .tar.gz files. Can someone help here please....

Dear List,   I have some longitudinal data, each patient was followed at times 0, 12, 16, 24 weeks and measure severity of a illness (0-worse, 1-same, 2-better). So, longitudinal response is categorical.  I was wondering whether lmer in R can fit a model for this type of data. If so, how we code? Or any other function in R that can fit this type of longitudinal data? Any suggestion would be

Hi   I am using following code to produce a xyplot for some longitudinal data. There are 2 panels. It produced all longitudinal trajectories with mean profile. But since the dataset it very large plot looks very messy. I want to show, say 10 randomly selected individual longitudinal trajectories together with mean profile for entire dataset. Could any help me to alter the following code to do

Hi, I need to fit model using crr, however my covariate is categorical with 3 levels. I use crr(time,status,agesplit,failcode=1,cencode=0) where agesplit is defined as <20,21-29,>30 years, so it takes 0, 1 or 2 for each patient. I hoped to get estimated coefficients for the levels 1 and 2 w.r.t level 0 as in coxph. But, I didn't. Could someone please help me to use crr in this

Dear all, I am using "coxme" function in Kinship library to fit random treatment effect nested within centre. I got 3 treatments (0,1,2) and 3 centres. I used following commands, but got an error. > ugroup=paste(rep(1:3,each=3),rep(0:2,3),sep='/') > mat1=bdsmatrix(rep(c(1,1,1,1,1,1,1,1,1),3),blocksize=rep(3,3),dimnames=list(ugroup,ugroup)) >

Dear R users,   I want to compute the 95% CI for difference in median survival times of two treatment groups. survfit function in R gives median and the corresponding CIs for each group. Could you please help me to get a CI for the difference in median times?   Thanks Ruwanthi [[alternative HTML version deleted]]