similar to: p-value for hazard ratio in Cox proportional hazards regression?

Dear all, this is my first message to this mailing list - please advise if it is not the right place for the subject I've been using R very intensively the last 3-4 years and one of the most tedious tasks is modification of lookup or conversion tables So far, I have not found functions that create the commands for creating objects (vectors, data frames) based on the objects themselves -

Hi, I managed to install 2.6.0 on a Gentoo system and almost everything is functioning properly with the usbhid-ups driver. I had to add "productid = 0004" into my ups.conf. For monitoring and administration, I use the cgi interface. I have problems with the instant commands tough: The commands seem to have no effect most of the times (except see next paragraph), despite the response

Hi, I have some general questions about statistical analysis for a research dataset and a request for advice on using R and associated packages for a valid analysis of this data. I can only pose the problem as how to run multiple ANOVA tests on time series data, with reasonable controls of the family-wise error rate. If we run analysis at many small sections of a long time-series, the Type-I

Hi I have been asked to perform a multivariate survival analysis with competing risks. We used to use the Cox Regression from SPSS. To perform this new analysis I'm using the comp.risk function from the timereg package. I have managed to use it and get the final model and the correct P values, but I cannot find anything like the Exp(B) (the Hazard Ratio) in the function's result. Anyone

Hi useRs, Many studies of the link between red meat and colorectal cancer use Cox proportional hazards with (among other things) a gender covariate. If it is true that men eat more red meat, drink more alcohol and smoke more than women, and if it is also true that alcohol and tobacco are known risk factors then why does it make sense to "adjust" for gender? I would think that in this

I am trying to run a Cox regression (coxph) to predict survival after surgery and xray therapy. The model violates the proportionality assumption (tested using time-dependent covariates). I have tried to use strata to solve the problem but the stratified model still violates the assumption. Does the violation of proportionality preclude use of a Kaplan-Meier analysis? Is there any other possible

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,

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.

Dear List, Is the test for proportional hazards valid when the model contains a cluster variable? The output looks strange with the cluster variable. My intervals are based on calendar time and the clustering variable is related to the season the event occurs in. model1<-coxph(Surv(Start,Stop,Event)~LagAOO+I(LagAOO^2)+ FirstSeen+TSLE+strata(CumPOO.rc)+cluster(quarter),data=data8, x=T)

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] <-

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

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

Hi I'm trying to interpret the output from the coxph command. One of the outputs is: Rsquare= 0.01 (max possible= 0.069 ) Given that the methods for calculating R squared and its validity with proportional hazards regression are debated in the literature - can anyone tell me exactly how this part of the coxph output is calculated and how I derive my R-squared from it? Thanks Helen

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 =

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 =

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

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