similar to: Stats question - cox proportional hazards adjustments

library(glmpath) data(heart.data) # heart.data is a list, $y a vector, $x a matrix data <- data.frame(x=I(heart.data$x), y = heart.data$y) > data[1:2,] x.1 x.2 x.3 x.4 x.5 x.6 x.7 x.8 x.9 y 1 160 12 5.73 23.11 1 49 25.3 97.2 52 1 2 144 0.01 4.41 28.61 0 55 28.87 2.06 63 1 > dimnames(heart.data$x)[[2]] [1] "sbp"

Dear UseRs, Suppose I have data regarding smoking habits of a prospective cohort and wish to determine the risk ratio of colorectal cancer in the smokers compared to the non-smokers. What do I do at the end of the study with people who die of heart disease? Can I just censor them exactly the same as people who become uncontactable or who die in a plane crash? If not, why not? I'm thinking

Hello all I would like to visualize the hazard ratios of a cox proportional hazards model. I have seen some good examples in the New England Journal of Medicine: http://content.nejm.org/cgi/content/short/353/26/2747/F3 http://content.nejm.org/cgi/content/short/350/26/2654/F2 (I hope these are open access, but I am not sure) And something similar in the book 'R Graphics' by Paul

Hello, I need to implement variable selection procedures (such as stepwise and backward selection) in Cox proportional hazards model, but can't seem to find an R or S-plus command for these procedures. I am aware that these can be done in SAS. I would appreciate help from anyone who knows how to implement these procedures in Cox models using S-plus or (preferably) R. Thanks! Regards,

Good afternoon, I am currently trying to do some work on survival analysis. - I hope to seek your advice re: 2 questions (1 general and 1 specific) (1) I'm trying to do a stratified Cox analysis and subsequently plot(survfit(object)). It seems to work for some strata, but not for others. I have tumor grade, which is a range of 1 - 4. When I divide this range of 1:4 into 2 groups, it

I know that mvrnorm from MASS (generously provided by Profs. Venables and Ripley) can be used to generate multivariable normal data that can be used in a linear regression with certain desired characteristics (e.g. a given mean for each variable as well as a given variance-covariance pattern). Is there any similar facility that can be used to generate data for (1) a logistic regression and (2) a

I would like to perform a permutation test for Cox proportional hazards regression model. I only find it for t-test and other tests (e.g. comparing two medians). Is there a way that I can perform a Cox PH model in R or SAS for the LR-test? I am doing the following B <- 1000; LRtestx <- rep(NA,B); Srv <- Surv(Time, Event); for(j in 1:B){ LRtestx[j] <-

Dear All, I am contemplating centering the covariates in my Cox model to reduce multicollinearity between the predictors and the interaction term and to render a more meaningful interpretation of the regression coefficient. Suppose I have two indicator variables, x1 and x2 which represent age categories (x1 is patients less than 16 while x2 is for patients older than 65). If I use the following

Hi. I used coxph(surv(start,end,event)~~event,data) to deal with interval censor data. Does anyone know similar samples using coxph(surv(start,end,event)~~event,data)? If you knows, can you tell me? I'll really appreciate it. Thank you very much R learner.

I am calculating cox propotional hazards models with the coxph function from the survival package. My data relates to failure of various types of endovascular interventions. I can successfully obtain the LR, Wald, and Score test p-values from the coxph.object, as well as the hazard ratio as follows: formula.obj = Surv(days, status) ~ type coxph.model = coxph(formula.obj, df) fit =

Hello, My advisor and I have been working on some survivorship analyses in R and we are hoping to get some feedback on a particular issue involving nesting. We are interested in patterns of food discovery by ant species. Our observations consist of time to discovery by an ant for three different food types, each of two different sizes. These data were collected at 6 plots located in each of

I'm getting unexpected results from the coxph function when using weights from counter-matching. For example, the following code produces a parameter estimate of -1.59 where I expect 0.63: d2 = structure(list(x = c(1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1), wt = c(5, 42, 40, 4, 43, 4, 42, 4, 44, 5, 38, 4, 39, 4, 4, 37, 40, 4, 44, 5, 45, 5, 44, 5), riskset =

timh at insightful.com wrote: > library(glmpath) > data(heart.data) > # heart.data is a list, $y a vector, $x a matrix > data <- data.frame(x=3DI(heart.data$x), y =3D heart.data$y) > =20 >> data[1:2,] >> =20 > x.1 x.2 x.3 x.4 x.5 x.6 x.7 x.8 x.9 y > 1 160 12 5.73 23.11 1 49 25.3 97.2 52 1 > 2 144 0.01 4.41 28.61

Hi, I'm new to R and using it for Cox survival analysis. Thanks to this great forum I learned how to compute the HR with its confidence interval. My question would be: Is there any way to get the p-value for a hazard ratio in addition to the confidence interval? Thanks, Thierry -- Thierry Panje Visiting Student Researcher Department of Psychology Stanford

I have data in a file named hands.dat, which is given at the end of this question. (It's from a stats textbook example on anova). I'd like to do an aov on this, which I guess would be d <- read.table("~/hands.dat", header=TRUE) aov(Bacterial.Counts ~ Water + Soap + Antibacterial.Soap + Alcohol.Spray, data=d) but this fails. Do I need to break d$Method up into columns for

Hello Everyone,   I'm learning how to perform various statistical analyses in R. I'm checking my understanding by replicating examples from my SAS books. Below is an attempt to replicate a Cox Proportional Hazards model with a time-varying covariate. I think I'm doing this correctly but am not completely sure. I would appreciate it if someone could double-check my results. In case

Buenas. Abajo pongo la salida de un modelo de cox , dónde he estratificado por una variable de país (Countryb) y por otra (Q6). Además hay interacción entre la variable mobilityPDurG2 (es una variable 0,1, y 0 es la categoría de referencia) país. La categoría de referencia para país es "united kingdom". Mi duda surge si quiero calcular el hazard ratio para los que tienen un 1

the data is : >table.8.3<-data.frame(expand.grid( marijuana=factor(c("Yes","No"),levels=c("No","Yes")), cigarette=factor(c("Yes","No"),levels=c("No","Yes")), alcohol=factor(c("Yes","No"),levels=c("No","Yes"))), count=c(911,538,44,456,3,43,2,279))

In your particular case I don't think that censoring is an issue, at least not for the reason that you discuss. The basic censoring assumption in the Cox model is that subjects who are censored have the same future risk as those who were a. not censored and b. have the same covariates. The real problem with informative censoring are the covaraites that are not in the model; ones that

On 16 Apr, Unung Istopo Hartanto asked about using R library 'foreign' to import SPSS Data Entry data files. SPSS Data Entry is an application that allows for the creation of formatted data entry forms (as does EpiInfo, Epidata and CSPro (all free downloads)). As such it creates the usual SPSS data files, but adds forms information, which the 'foreign' package does not know how