similar to: Forced inclusion of varaibles in validate command as well as step

Hello, I use rpart to predict survival time and have a problem in interpreting the output of ?estimated rate?. Here is an example of what I do: > stagec <- > read.table("http://www.stanford.edu/class/stats202/DATA/stagec.data", > col.names=c("pgtime", "pgstat", "age","eet", "g2", "grade", "gleason", >

hello, i'd appreciate help with my glmer. i have a dependent which is an index (MH.index) ranging from 0-1. this index can also be considered as a propability. as i have a fixed factor (stage) and a nested random factor (site) i tried to model with glmer. i read that it's possible to use a quasibinomial distribution, for this kind of data, which i than actually did - but firstly (1)

Hello all I am a very new R user I am used to using STATA My problem: I want to build a Cox model and validate this. I have a large number of clinical relevant factors and feel the need to reduce these. Meanwhile I have some clinical variables I deem sufficiently important to force into the model regardless of AIC or p value. This is my present log over commands

I'm trying to use a contributed package (rmetasim) to generate simulated genetic datasets. My scripts work fine when I run them on a Sun workstation running Solaris 7 and when I run them on a ~4 year old laptop PC that I have. However, when I run them on my new laptop (Dell Latitude D410 purchased in August 2005), the simulation will run for a short (variable) period of time, then R

I realized that the script I included in my original post (see below) was written for an older version of rmetasim and will not work with the current version. The only change that need be made to get my script to run with the latest release of rmetasim is to change the command 'simulate.landscape()' to 'sim.landscape()'. My apologies to anyone who tried to use my script and

Greetings guRus -- If a variable, e.g., 'varname', is a character string, e.g. varname <- "datavector", and I want to apply a function, such as table(), to datavector, what syntax or method will do so using only the variable varname? This seems similar to indirect addressing, but I have not seen a method for it in the R manuals. Is there a general name for such indirect

Hello, I have simulated 30 observations from a binomial(5,0.1) distribution. Now I need to make frequency table( that means I need to tally how many 0's , 1's 2's....... 5's) I know that the simple R function table() will do this, but I am afraid that some times I may get zero frequency for some particular values (for example in the above there are 5-0's 10-1's ,

I would like to produce a bar plot with varying-width bars. Here is an example to illustrate: ww <- c(417,153,0.0216,0.0065,556,256,0.0162,0.0117, + 726,379,0.0358,0.0501,786,502,0.0496,0.0837, + 892,591,0.0785,0.0795) yy<-t(t(array(ww,c(2,10)))) barplot(yy[,2*1:5],las=1,space=c(.1,.5),beside=T) produces a barplot of 5 pairs of bars that are of equal width

I am receiving the above error ( full r session output below) the script runs OK in windows. and "genotypes" and "ploidy" are both correct arguments any suggestions would be most welcome Nevil Amos MERG/ACB Monash University School of Biological Sciences > library(Geneland) Loading required package: RandomFields Loading required package: fields Loading required

Hi Guys, I have this part of a program: library(survival) Gastric <- cbind.data.frame(Gp=c(rep(1,45),rep(0,45)), ### 2nd gp 0 time=c(1,63,105,129,182,216,250,262,301,301,342,354,356,358, 380,383, 383,388,394,408,460,489,499,523,524,535,562,569,675,676, 748,778,786,797,955,968,1000,1245,1271,1420,1551,1694,2363,2754,2950,

Hello, I am working with a matrix of multilocus genotypes for ~180 individual snail samples, with substantial missing data. I am trying to calculate the pairwise genetic distance between individuals using the stats package 'dist' function, using euclidean distance. I took a subset of this dataset (3 samples x 3 loci) to test how euclidean distance is calculated: 3x3 subset used

CRAN (and crantastic) updates this week New packages ------------ * allan (1.0) Alan Lee http://crantastic.org/packages/allan Automates Large Linear Analysis Model Fitting * andrews (1.0) Jaroslav Myslivec http://crantastic.org/packages/andrews Andrews curves for visualization of multidimensional data * anesrake (0.3) Josh Pasek http://crantastic.org/packages/anesrake This