similar to: Estimating correlation in multiple measures data

Dear R-Helpers, I am a novice in survival analysis. I have the following code: for (i in 3:12) print(coxph(Surv(time, status)~a[,i], data=a)) I used it to fit the Cox Proportional Hazard models separately for every available parameter (columns 3:12) in my data set - with intention to compare the Hazard Ratios. However, some of my variables are in range 0.1 to 1.6, others in range 5000 to

Dear R-helpers, I am working with 'cph' models from 'rms' library. When I build simple survival models, based on 'Surv(time, event)', everything is fine and I can make nice plots using plot(Predict(f, time=3)). However, recently I tried to be more specific and used 'Surv(start, stop, event)' type model. Using this model 'plot(Predict(f))' works OK, but

Hello, I have made an R script that prepares a NONMEM dataset and I would like to start the NONMEM run right after the dataset is ready. I am using windows XP, R 2.9.1 and NONMEM 6. I have prepared a run.bat file that looks like this: ---------------------------------------- call K:\nmvi\NMdirectories.bat call K:\nmvi\nmfe6 "path\control.txt" "path\output.txt"

Hi everyone, have a small problem trying to converting a dataset in matrix form to an array. Specifically: data include 3D measurement -x,y,z of 59 points in 36 objects. They are stored as a matrix (x) of 2124 rows and 3 columns. What I want to do is to extract each subject's dataset using an array (b). Accordingly, I tried the following command: b<-array(a,c(59,3,36)). The problem is

Dear R-Helpers, I'm working with immunoassay data and 5PL logistic model. I wanted to experiment with different forms of weighting and parameter selection, which is not possible in instrument software, so I turned to R. I am using R 2.14.2 under Win7 64bit, and the 'nls' library to fit the model - I started with the same model and weighting type (1/y) as in the instrument to see

Dear R-helpers and graphics gurus, I have two problems with plotting confidence bands: 1. First is relatively simple. I am using the Passing-Bablok procedure to obtain "unbiased" regression coefficients. This procedure yields the "a" & "b" coefficient values along with their confidence intervals. I then plot the raw data with the regression line, but I would

Dear R-helpers I have a data set of roughly 10 million records, 7 columns. It has only about 500MB as a csv, so it fits in the memory. It's painfully slow to do anything with it, but it's possible. I also have another dataset of covariates that I would like to explore - with about 4GB of data... I would like to merge the two datasets and use lmer to build a mixed effects model. Is

Dear R-helpers, I am developing a Mixed-Effects model for a study of immunoassays using 'lme4' library. The study design is as follows: 10 samples were run using 7 different immunoassays, 3 times each, in duplicates. Data attached. I have developed the following model: c.lme <- lmer(Result~SPL + (SPL|Assay/Run) -1, data=data) This model has excellent predictions - the Rsquared of

Dear R-helpers I am running a simple mixed effects model using lme(). The call looks like this: fit <- lme(Analyte~Sample, data=Data, random=~1 | Run) I am particularly interested in the estimated random effects. When I print the 'fit' object, it looks something like example below: (...) Random effects: Formula: ~1 | Run (Intercept) Residual StdDev: 3.483794 3.637523

Hello everyone, I am new to R, I have been using SAS for a while. Not surprisingly, I find R much better in graphics, which is publication ready right away. Recently, I have been trying to calculate some basic statistics using R. I have a dataset of multiple rows per subject. For example: Subject Date Factor1 Factor2 Factor3 P1 0.5 1 1 3 P1 1 3 2 5 P1 2 3 5 NA ... P2 0.5 1 6 4 P2 1 2 NA 7 P2

Hello all, I am trying to optimize my logistic regression model by using bootstrap. I was previously using SAS for this kind of tasks, but I am now switching to R. My data frame consists of 5 columns and has 109 rows. Each row is a single record composed of the following values: Subject_name, numeric1, numeric2, numeric3 and outcome (yes or no). All three numerics are used to predict

Hello R-helpers, I have a problem with formatting a single number to show leading zeros. For example, I want "2" displayed as "002". My numbers have 1 to 3 digits and I would like them all to display 3 digits for printing. I know I could use "paste" in a loop with several "if"s, but I was wondering if there is a single function that can do this. I have

I think the argument supporting the use of bootstrap to determine coefficients, as opposed to just running linear regression on the whole dataset, is the comparison of Rsq and prediction errors between these two approaches - page 1502. There's a substantial difference in favor of the bootstrap approach. -- Michal J. Figurski Gustaf Rydevik wrote: > The url for the mentioned paper is

Hi, Is there anyone know if BUGS language allows the combination of variables as response such as Y[i] <- a*X1[i]+b*X2[i] Y[i] ~ dnorm(c,d) It seems doesn't work in my model. The problem is between two ######. The error message is > modelCheck("BayesBioMarker.BUGS") model is syntactically correct > modelData(paste("BUGS_data.txt",sep="")) data

Hello All, I am trying to compile Samba on POSIX under OpenVMS on a DEC 2000 AXP, however I am having difficulty defining the right FLAGSM and LIBSSM in the Makefile. So thus I'm having trouble getting the correct #includes, can anyone help? Regards, Gavin Butler -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: application/ms-tnef

Thank you Frank and all for your advices. Here I attach the raw data from the Pawinski's paper. I have obtained permission from the corresponding Author to post it here for everyone. The only condition of use is that the Authors retain ownership of the data, and any publication resulting from these data must be managed by them. The dataset is composed as follows: patient number / MMF dose in

Hai, ? Can somebody try to run : ? samba-tool time and samba-tool time servername.fqdn ? when i run it, im getting : ? ERROR(runtime): uncaught exception - Connection to SRVSVC pipe of server 'rotterdam.bazuin.nl' failed: NT_STATUS_NONE_MAPPED ? File "/usr/lib/python2.7/dist-packages/samba/netcmd/__init__.py", line 175, in _run ??? return self.run(*args, **kwargs) ? File

Dear R-helpers, I have a dataset named "qu", organized as follows: Sample Run Replicate Value 1 1 1 25 1 1 2 40 1 1 3 33 1 1 4 29 1 2 1 37 1 2 2 44 1 2 3 45 1 3 1 25 1 3 2 40 1 4 1 33 1 4 2 29 1 4 3 25 2 ... Basically, a sample was run on an assay multiple times within a single day. Each of these results is "Replicate". Then run was repeated several times in

Hi - sorry to intrude, but can somebody point me to a suitable mailing list where a tyro can get some advice on modifying an existing llvm llvm assembler ... rather lightly? I want to add an extra instruction to the assembler/machine code supported by the OR1K llvm port. Well, there are a few more things I need to do, but that will be good enough to start with! I was able to what I wanted

Hello, For some analysis of a mesh structure I need to prepare several vectors of indexes of different length. This is done by the following code sequence (including diagnostic output): #-------------------------------------------------- MT_ind <- which(V1.frame[,2] %in% mm[,1]) print("M_ind") str(M_ind) Q1_ind <- which(V1.frame[,2] %in% mq1) print("Q1_ind")