search for: stratifying

>Hello, I am hoping for assistance in regards to examining the contribution of stratified variables in a cox regression. A previous post by Terry Therneau noted that "That is the point of a strata; you are declaring a variable to NOT be proportional hazards, and thus there is no single "hazard ratio" that describes it". Given this purpose of stratification, in the

Hello, I am using Dr. Harrell's design package to make a nomogram. I was able to make a beautiful one without stratifying, however, I will need to stratify to meet PH assumptions. This is where I go wrong, but I'm not sure where. Non-Stratified Nomogram: f<-cph(S~A+B+C+D+E+F+...

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

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

Hi all: For stratified count data,how to perform regression analysis? My data: age case oc count 1 1 1 21 1 1 2 26 1 2 1 17 1 2 2 59 2 1 1 18 2 1 2 88 2 2 1 7 2 2 2 95 age: 1:<40y 2:>40y case: 1:patient 2:health oc: 1:use drug 2:not use drug My purpose: Anaysis whether case and

Dear R community, I have data on beta&standard error (for the main effect of variable x), stratified by sex for my dataset. I wish to calculate the sex-interaction effect (as beta&se) from these two stratified datasets. Is there a package to do this? If not, any advice how to do it manually? Thank you very much and best regards, Georg. ************************ Georg Ehret, JHU,

This is a follow-up to a query that was posted regarding some problems that emerge when running anova analyses for cox models, posted by Mathias Gondan: Matthias Gondan wrote: >* Dear List,*>**>* I have tried a stratified Cox Regression, it is working fine, except for*>* the "Anova"-Tests:*>**>* Here the commands (should work out of the box):*>**>*

Hi All, I'm trying to automate a data summary using summary or describe from the HMisc package. I want to stratify my data set by patient_type. I was hoping to do something like: Describe(myDataFrame ~ patient_type) I can create data subsets and run the describe function one at a time, but there's got to be a better way. Any suggestions? Rachel [[alternative HTML

Dear experts, I am asking for help with a question regarding to stratified bootstrap. My dataset is a longitudinal dataset (3 measurements per person at year 1, 4 and 7) composed of multiple clinic centers and multiple participants within each clinic. It has missing values. I want to do a bootstrap to find the standard errors and confidence intervals for my variance components. My model is a

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

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

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'

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?m trying to set up proportional hazard model that is stratified with respect to covariate 1 and has an interaction between covariate 1 and another variable, covariate 2. Both variables are categorical. In the following, I try to illustrate the two problems that I?ve encountered, using the lung dataset. The first problem is the warning: To me, it seems that there are too many dummies

Dear List, I have tried a stratified Cox Regression, it is working fine, except for the "Anova"-Tests: Here the commands (should work out of the box): library(survival) d = colon[colon$etype==2, ] m = coxph(Surv(time, status) ~ strata(sex) + rx, data=d) summary(m) # Printout ok anova(m, test='Chisq') This is the output of the anova command: > Analysis of Deviance Table

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

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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]]

Hello, I am using Dr. Harrell's design package to make a nomogram. I was able to make a beautiful one. However, I want to change 5-year survival probability to 5-year failure probability. I couldn?t get hazard rate from Hazard(f1) because I used cph for the model. Here is my code: f1 <- cph(Surv(retime,dfs) ~ age+her2+t_stage+n_stage+er+grade+cytcyt+Cyt_PCDK2 , data=data11, surv=T,

Hi, I’m new to R (just installed today) and I’m trying to figure out how to do stratified randomisation using it. My google search expedition has lead me to believe that blockrand package will most probably be the answer to it. I’ve played around with blockrand for awhile and tried the sample code: library(blockrand) ##stratified by sex male <- blockrand(n=100,