similar to: Software for Epidmiological, Longitudinal Data

Dear List, I have a theoretical question related to epidemiological data analysis: If the treatment status (tx = 0,1) changes over time for the patients in a non-randomized cohort, is there a way to estimate the treatment effect? (i.e., after joining the study, some patients may have to wait for a period of time before receiving the treatment, i.e., the situation of patient with id == 2 for the

Dear R-list member, I'm using the function pmnorm() (-->library(mnormt)) within a for-loop. Certain parameter values leads to an error message: "(In sqrt(diag(S)) : NaNs produced, In sqrt(1/diag(V)) : NaNs produced, In cov2cor(S) : diag(.) had 0 or NA entries; non-finite result is doubtful)" obviously because "NaNs" were produced. Is it possible to tell R that it

Dear R-List member, tried implement the foreach loop. It works fine, when I'm using %do%, but not when I'm using %dopar%. I always receive one of the following error messages: error in { : task 1 failed - "Objekt 'S3' not found" - could the .export be an solution for this?? Any help is much appreciated! The Code hast the following structure: ########## dft3 =

Dear R-List member, I have a problem when I'm trying to save two arrays from a foreach-loop. I'm also not sure whether this is possible or just my inexperience. However, this works perferctly fine with a for-loop. Here is an example code - any help is much appreciated!!: ############ n.vpn = 2 n.run= 3 # create to empty matrices sme = matrix(NA,4,n.vpn) test = matrix(NA,4,n.vpn) #

Dear list member, I struggle with the problem, why the probabilities of choosing one of three mutually exclusive alternatives don?t sum up to 1! Let?s assume we have three alternatives X, Y, and Z. Let?s further assume we know their respective utilities: uX, uY, uZ. I?m interested in calculating the probability of choosing X, Y, and Z. Since I assume that the alternatives are mutually

Dear All, discussing with a statistician of a pharmaceutical company I received this answer about the statistical package that I have planned to use: As R is not a validated software package, we would like to ask if it would rather be possible for you to use SAS, SPSS or another approved statistical software system. Could someone suggest me a 'polite' answer? TIA Giovanni -- dr.

Hello List, I am new to R and statistics in general. My two colleges and I would like to get some training in the proper usage of R. A quick internet search provided no results for the region of Basel in Switzerland. Does some one on this list knows of any trainers or schools in the region in question or where to look next? Regards, Dominik Riva Universitätsspital Basel Med.

Hi all, Mango have released their updated training schedule which includes new courses and new locations. Hadley Wickham will also be coming to London to teach Data Visualisation in R. Please see details below: Public Courses Our public courses include introductory to advanced training in general data analysis through to industry specific data analysis. Attendees of our public courses receive

Hi all, I a semi-beginner with R and I am working with the plm package to examine a longitudinal dataset. Each individual in this dataset has a longitudinal weight for the probability that he or she remains in the sample. Unfortunately, I have not found an argument to use weights in the plm function? I tried ?weights=? like in standard lm or in nlme or lm4 but it does not work. I asked the

With the support of the R Foundation Conference Committee, we are happy to announce the promotion of regional R events to connect our R community and bridge us till useR! 2024. On July 21st we hold an event in Basel, with all ticket sales for the Basel event being directly donated to the R Foundation. Similar events are being planned in Shanghai and San Francisco this summer. Basel event link

With the support of the R Foundation Conference Committee, we are happy to announce the promotion of regional R events to connect our R community and bridge us till useR! 2024. On July 21st we hold an event in Basel, with all ticket sales for the Basel event being directly donated to the R Foundation. Similar events are being planned in Shanghai and San Francisco this summer. Basel event link

Hi all: I have a question about the sample size calculation. It's a pilot study,which includes 2 groups(low,high),3 time point(3,6,9 monthes).Each person has 3 results which according to the 3 time points.So it's a longitudinal study. I want to calculate the minimum sample size from the pilot study, but can't find the solution since the data is highly skewed and it's a

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

Dear R-Users! Is there a possibility in R to do analyze longitudinal survey data (repeated measures in a survey)? I know that for longitudinal data I can use lme() to incorporate the correlation structure within individual and I know that there is the package survey for analyzing survey data. How can I combine both? I am trying to calculate design-based estimates. However, if I use svyglm() from

i am studying Longitudinal Data Analysis and want to carry it with R.anyone knows any materials about Longitudinal Data Analysis with R in the internet which i can download? thank you.

Hi, does anyone out there have a recommendation for multilevel / random effects and longitudinal analysis? My dream book would be something that's both accessible to a non-statistician but rigorous (because I seem to be slowly turning into a statistician) and ideally would use R. Peter

Dear R people, I have a matrix like this: var1 var2 var3 var4 a1 7.1 7.2 8.1 8.2 a2 10.5 10.6 ... ... a3 b1 b2 b3 b4 c1 c2 ... The matrix row names are "a1", "a2", ...... and the matrix column names are "var1", "var2", "var3" and "var4". Now I want to reshape this data into a

Hi, Can one tell me which procedure will fit an ordinal logistic regression model for longitudinal data set. To be precise, I have both dichotomous and polytomous items. Also, I would like to specify different covariance structures (unstructured, ar1 etc) for trial runs. Thanks -- View this message in context:

Dear R-help subscribers, I use xyplot to plot longitudinal data as follows: score<-runif(100,-4,5) group<-sample(1:4,100,rep=T) subject<-rep(1:25,4) age<-rep(runif(4,1,40),25) df<-data.frame(score,group,age,subject) xyplot(score~age|group, group=subject, panel=function(...){ panel.loess(...,lwd=4) panel.superpose(...)} ,data=df) this produced a plot with four panels one for each

Hi everyone I have the following problem: My dataframe has 3 variables: ID, Year and and an outcome variable. The dataframe contains repeated measurements because the subjects filled out a questionnaire every year. The time span covers 2 years. Now I want to check if there is a significant change in the outcome over the 2 years with a paired wilcox.test. The problem: Not every subject