similar to: create stratified splits

Hello list, I have the following function which, as you can see, uses mean: meanratings <- round(apply(stack03[,c(102:121)],2,function(x) (tapply(x ,actcode, mean, na.rm=T))), digits=1) The above function yields the following output: q27a q27b q27c q27d q27e q27f q27g q27h q27i q27j q27k q27l q27m q27o q27p 1 7.8 8.1 7.7 7.9 7.9 NaN NaN 8.4 7.8 7.0 7.6 NaN NaN 7.1 6.0 2

Hello everyone, I am a new user of R. Does anybody know how hazard ratios are extracted for each factor level in a stratified Cox proportional hazard regression model? I have a cancer data set where the variable ?differentiation? is a factor with three levels: poor, intermediate and good. I would like to extract the hazard ratio for each grade level and relate it to another prognostic factor.

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Hello, I'm fitting poisson regression to mortality data and wish to stratify by age. Is there any way to perform this stratification and use the glm function in R? Thanks, Hannah Murdoch

Dear All, is there a stratified version of the Wilcoxon test (also known as van Elteren test) available in R? I could find it in the survdiff function of the survival package for censored data. I think, it should be possible to use this function creating a dummy censoring indicator and setting it to not censored, but may be there is a better way to perform the test. Thanks, Heinz T??chler

I was trying to do a bunch of planned contrast but ran into a snag. fit.contrast won't work with an Error term in aov. Ok, then I use lme. Only, now it seems there is no way to enter the interaction terms (something like "x1:x2"). I couldn't find a way to use the interaction term in the help. Is there an undocumented method or some other command for planned contrasts?

Hello, I have been informed that there is no R package for the stratified Wilcoxon's rank sum test (Van Elteren's test) with the locally best weights. I need to use the alternative test to a clinical endpoint where the distribution approximate normal distribution, and compare to the regular ANOVA. I have been directed to use SAS with PROC FREQ with the SCORES=modridit option and CMH2

Dear All, I was writing a small wrapper to bootstrap a classification algorithm, but if we generate the indices in the "usual way" as: bootindex <- sample(index, N, replace = TRUE) there is a non-zero probability that all the samples belong to only one class, thus leading to problems in the fitting (or that some classes will end up with only one sample, which will be a problem

Using R version 1.8.1 for Windows, I obtain an error message using the following code. The data frame was constructed in the counting process style, where V1 is the start time, V2 is the stop time, and V3 is the censoring indicator. There are no zero-length time intervals. Variable V4 is the stratification factor (gender: F,M). S<-Surv(V1,V2,V3) fit<-survfit(S ~ V4,data=test.dat)

Hello, I am new to R, and am having trouble getting the output I want from a stratified bootstrap. I didn't recieve a reply the first time I posted this question so I have tried to make it more clear. My data frame (denboot) is set up as follows: SITE cswa parea treat 1 BeanA 3 1.20 m 2 BeanBC 3 1.05 m 3 BeanD 1 0.93 m 4 BlackB 1 1.01

Hi, Is there a way to do stratified cross-validation of Support Vector Machines? Regards, Kaustubh ____________________________________________________________________________________ the tools to get online. [[alternative HTML version deleted]]

Given a set of data with a number of variables plus a response, I'd like to obtain a randomized subset of the rows such that the marginal proportions of each variable are maintained closely in the subset to that of the dataset, and possibly maintaining as well the two-factor interaction marginal proportions as well for some pairs. This must be a common problem in data mining, but I

Hi, does anyone know of a function to calculate odds ratios in multiway tables (stratified) (+ the other usual statistics involved) i mean: say we have a table r*c*d, For every d (depth) we have a r*c table, and in this table the odds ratio's are calculated for every 2*2 subtable in it. logically this function would look like): ORs(multiwaytable) or ORs(data$var1r,data$var2c,data$var3d)

Hi All: Could anyone point me to a package that can calculate stratified kappa? My design is like this, 4 raters, 30 types of diagnosis scores, 20 patients. Each rater will rate each patient for each type of diagnosis score. The rater's value is nominal. I know I can measure the agreement between raters for each type of diagnosis score, e.g., calculate out 30 kappa values. My problem is I

Dear all, I used cph() function from Frank harrell's Design package to create a survival model, then used functions 'Function' and 'sascode' to generate prediction equation based on the saved survival model. But it failed. I included a stratified variable in the model. If I removed the stratification, they were working well. Does that mean that function 'Function'

Rers: What is the preferred library/function for doing stratified random sampling from a dataset, given I want to control the number of samples (rather than the proportion of samples) per strata? Thanks! --j -- Jonathan A. Greenberg, PhD Postdoctoral Scholar Center for Spatial Technologies and Remote Sensing (CSTARS) University of California, Davis One Shields Avenue The Barn, Room

Dear R-List,   I would like to have a large number of stratified random subsamples drawn from my dataframe and automatically test for correlation differences in every subsample.   Let this be my dataframe   df<-data.frame(group=c(rep(1,5),rep(2,5),rep(3,5)),a=c(3,4,5,6,3,4,5,4,5,4,1,2,1,2,1),b=c(1,2,3,4,5,3,4,3,4,5,6,5,6,2,3),c=c(2,2,3,3,5,1,1,6,6,5,6,1,1,2,1))   Then I would like to have n

Hi All, I'm using R's randomForest package (and it's quite awesome!) but I'd really like to do some stratified sampling with a regression problem. However, it appears that the package was designed to only accommodate stratified sampling for classification purposes (see https://stat.ethz.ch/pipermail/r-help/2006-November/117477.html). As Andy suggests in the link just

Hi, Has anyone done (or know of) any nice R activities that help introductory students ( and teachers :) ) better understand the concepts of simple vs stratified vs cluster sampling? Any links? David -- View this message in context: http://r.789695.n4.nabble.com/SRS-Stratified-and-Cluster-sampling-tp4655099.html Sent from the R help mailing list archive at Nabble.com.

I am having trouble doing a stratified analysis while obtaining the mean,median, and standard deviation of each group. I have copied and pasted the console below. [[alternative HTML version deleted]]