similar to: Strata and Degrees of freedom in anova and multi-level modeling

>From e980153 Tue Mar 21 18:50:55 2000 To: bates@stat.wisc.edu Subject: Use of Rd2txt on .Rd files from rw-1.0.0 Files generated using prompt.data.frame() under rw-1.0.0 get scrambled (mildly) when I process them under Rd2txt on Solaris, (using R-devel 1.1.0). Files generated under R-devel 1.1 on Solaris are processed ok. The .Rd files from the two sources look identical. The problem is

Dear All, I got a warning message "X matrix deemed to be singular" in Cox model with a time dependent coefficient. In my analysis, the variable "SEX" is a categorical variable which violate the PH assumption in Cox. I first used the survSplit() function to break the data set into different time intervals, and then fit the model. The procedures can be described as follows:

ExpeRts, I'm trying to compare three survival curves using the function "survdiff" in the survival package. Following is my code and corresponding error message. > survdiff(Surv(st_months, status) ~ strata(BOR), data=mydata) Error in survdiff(Surv(st_months, status) ~ strata(BOR), data = mydata) : No groups to test When I check the "strata" of the variable. I get .

Dear list members, I am working with a Cox ph model for the duration of unemployment. The event of interest in my analysis is getting employed. I have various background variables explaining this event: age, sex, education etc. I have multiple unemployment spells per person. I use a model with person-specific frailty terms in order to take into account the correlation of spells by the same

Dear useRs, What is the syntax to obtain survival curves for single strata on many subjects? I have a model based on Surv(time,response) object, so there is a single row per subject and no start,stop and no switching of strata. The newdata has many subjects and each subject has a strata and the survival based on the subject risk and the subject strata is needed. If I do newpred <-

Hello, I'm using the package survey, version 3.22-2 in R 2.11.1, on windows XP, but this isn't a platform issue. I am trying to calculate some regression and probability proportional to size (pps) estimates for a dataset I have. The data has 2 strata, weights, and cluster IDs. However, I can't find a way to use multiple strata in the svydesign function. Currently, I'm ditching

Dear all, I have to select 122 stratified random samples from a population of >3900 cells. I have 41 strata and I have to draw a different number of samples from them(between 2 and 8). I have tried to apply the funtion strata following the instruction in the manual: strata(dataframe, stratanames=NULL, size, method=c("srswor"), pik,description=TRUE) but I get the error

Dear users, In a study with recurrent events: My objective is to get estimates of survival (obtained through a Cox model) by rank of recurrence and by treatment group. With the following code (corresponding to a model with a global effect of the treatment=rx), I get no error and manage to obtain what I want : data<-(bladder)

How can I get the log odds associated with the levels in strata() within a clogit() model? I'm running R-1.9.0 on a Linux platform. I am using clogit() to run a Rasch model in Item Response Theory in psychometrics. Symbolically, the model is: logit(p_{j,k}) = \log({\Pr(p_{j,k}) \over \Pr(1-p_{j,k})}) = \theta_j - \alpha_k, That is, the log odds of answering an test item correctly is

Dear All, I want to generate survival curve with cox model but I want to estimate the coefficients using glmnet. However, I also want to include a strata() term in the model. Could anyone please tell me how to have this strata() effect in the model in glmnet? I tried converting a formula with strata() to a design matrix and feeding to glmnet, but glmnet just treats the strata() term with one

My data.frame table consist of 3 variables (x,y and z) where each variable has 1000 units. I need to create 5 equal size strata according to one of the variable (let's say x) whereas units of x variable with a higher value have higher probability to be selected in a strata with a higher number (max strata number is 5). I've been trying different things so far and since I am fairly new to

Hi all, Had struggled in getting "Strata" in randomForest to work on this. Can I get randomForest for each of its TREE, to get ALL sample from some strata to build tree, while leaving some strata TOTALLY untouched as oob? e.g. in below, how I can tell RF to, - for tree 1 in the forest, to use only Site A and B to build the tree, while using the WHOLE Site C data for the oob error

[code]>require("survival") > coxph(Surv(futime,fustat)~age + strata(rx),ovarian) Call: coxph(formula = Surv(futime, fustat) ~ age + strata(rx), data = ovarian) coef exp(coef) se(coef) z p age 0.137 1.15 0.0474 2.9 0.0038 Likelihood ratio test=12.7 on 1 df, p=0.000368 n= 26, number of events= 12 > coxph(Surv(futime,fustat)~age, ovarian, subset=rx==1)

Hello All. I must be missing the really obvious here: mm <- function(d, i) median(d[i]) b1 <- boot(gravity$g, mm, R = 1000) b1 b2 <- boot(gravity$g, mm, R = 1000, strata = gravity$series) b2 Both b1 and b2 seem to have done (almost) the same thing, but it looks like the strata argument in b2 has been ignored. However, str(b1) vs str(b2) does show that the strata have been noted

Hello, I am new to R, and am having trouble running a stratified bootstrap. My data set consists of 38 study sites in which I recorded the number of bird pairs. Each site has been classified as burned or mowed and for each of these two strata I would like to determine the precision of an overall density estimate. I can run an unstratified bootstrap without problem, but when I specify the strata I

Dear R Group in package Deducer, how should i use the add.cross.strata.test() function to pass the chi.squared.test function as htest argument? ##########Example########### library(Deducer) dat<-data.frame(a=rnorm(100)>.5,b=rnorm(100)>0,c=rnorm(100)>(-.5)) tables<-contingency.tables( row.vars=a, col.vars=b, stratum.var=c,data=dat)

Hello: So i've fit a hazard function to a set of data using kmfit<-survfit(Surv(int, event)~factor(cohort)) this factor variable, "cohort" has four levels so naturally the strata variable has 4 values. I can use this data to estimate the hazard rate haz<-n.event/n.risk and calculate the cumulative hazard function by H<--log(haz) Now, I would like to plot this

First, I appoligise for the rooky question, but... I'm trying to obtain standard errors, confidence intervals, etc. from a sample design and have been trouble getting the results for anything other than the basic total or mean for the overall survey from the survey package. For example, using the following dataset, strata,cluster,vol A,1,18.58556192 A,1,12.55175443 A,1,21.65882438

Jorge: FYI, *generally speaking,* queries that are mostly statistical in nature, such as yours, are off topic here -- this list is about R programming help, not statistical help. Having said that, you still may get a useful response here -- the r-help/statistics intersection *is* nonempty. However, if not, 2.5 suggestions: 1. Try posting to r-sig-mixed-models instead. Repeated measures are a

Dear list users, I am trying to learn Repeated measures ANOVA using the aov() interface, but I'm struggling to understand its output. According to tutorials on the web, formula for a repeated measures design is: aov(Y ~ IV+ Error(SUBJECT/IV) ) This formula does work but it returns three strata (Error:SUBJECT, Error: SUBJECT:IV, Error: Within), when I would expect two strata (Within and