similar to: Using coxph with Gompertz-distributed survival data.

Hi all, Sorry if this has been answered already, but I couldn't find it in the archives or general internet. Is it possible to implement the gompertz distribution as survreg.distribution to use with survreg of the survival library? I haven't found anything and recent attempts from my side weren't succefull so far. I know that other packages like 'eha' and

Hello, all. I have co-opted a number of functions that can be used to plot the hazard/survival functions and associated density distribution for a Gompertz mortality model, given known parameters. The Gompertz hazard model has been shown to fit relatively well to the human adult lifespan. For example, if I wanted to plot the hazard (i.e., mortality) functions: pop1 <- function (t) {

Hi, I've been banging my head against the following problem for a while and thought the fine people on r-help might be able to help. I'm using the survival package. I'm studying the survival rate of a population with a preexisting linear-like event rate (there are theoretical reasons to believe it's linear, but of course it's subject to the usual sampling noise) Some of the

Dear All, I would like to fit some parametric survival models using left truncated, right censored data in R. However I am having problems finding a function to fit parametric survival models which can handle left truncated data. I have tested both the survreg function in package survival: fit1 <- survreg(Surv(start, stop, status) ~ X + Y + Z, data=data1) and the psm function in package

Hi, all. I'm working with published paleodemographic data (counts of skeletons that have been assigned into an age-range category, based upon observed morphological characteristics). For example, the following is the age distribution from a prehistoric cemetery in Egypt: naga <-

Hello. I am trying to write an R function to plot the survival function (and associated hazard and density) for a Siler competing hazards model. This model is similar to the Gompertz-Makeham, with the addition of a juvenile component that includes two parameters---one that describes the initial infant mortality rate, and a negative exponential that describes typical mortality decline over the

Dear All, I am trying to apply the function 'cox.zph' of the library survival, but I receive this error message: not found the object 'residuals.coxph'. I have re-installed the library 'survival' without any change and also a search with RSiteSearch was unsuccessful.. Any suggestion? TIA Giovanni PS: R 2.2.0 Windows XP HE dr. Giovanni Parrinello Section of Medical

Dear all! I tried to fit Gompertz growth models to describe cummulative germination rates using nls. I used the following code: germ.model<-nls(percent.germ~a*exp(-b*exp(-k*day)),data=tab,start=list(a=100,b=10,k=0.5)) My problem is that I want that the fitted model goes through the origin, since germination cannot start before the experiment was started, and y-max should be 100. Does anyone

Dear all, I use the Andersen plot to check for proportional hazards assumption for a factor (say x) in the Cox regression model and obtained a straight line that pass through the origin. However, the formal test done by the R-function cox.zph, which is based on the plot of Schonefeld residuals against time, indicates that proportional hazards assumption is violated. Further, a plot of the score

Hi, I wrote a function that worked well in R, but not in S-Plus, can anyone suggest a solution? > f.coxph.zph<-function(x) { cox.fit <- coxph(Surv(time.cox, status.cox) ~ x, na.action = na.exclude, method = "breslow") fit.zph<-cox.zph(cox.fit,transform='log') fit.zph$table[,3] } yyy is my data frame that contains survial time, censor status and predictor

Dear all, I have a question concerning the p-value. When running coxph I get a p-value = 0. :confused: Can this be true? Why aren?t there decimal points? Is there a way to find out the exact p-value? Here is the output: ---------------------------------------------------------------------------------------------------- Call: coxph(formula = Surv(start, stop, status) ~ Albumin_gproL, data = dial,

>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

> Dear All, > > I have built a survival cox-model, which includes a covariate * time interaction. (non-proportionality detected) > I am now wondering how could I most easily get survival predictions from my model. > > My model was specified: > coxph(formula = Surv(event_time_mod, event_indicator_mod) ~ Sex + > ageC + HHcat_alt + Main_Branch + Acute_seizure +

Hi all, Please help on this. We will be teaching epidemiology using opensource software. What are R built-in functions or functions in available packages that are capable of doing these: a) Logistic regression (glm?) b) Conditional logistic regression c) Logistic regression with random effects d) Beta-binomial regression e) Poisson regression f) Weibull regression (eha?) g) Exponential

Hi, r-help members. I have a question about summing two density distributions. I have two samples from which I've estimated hazard parameters for a Gompertz mortality model. With those parameters, I can calculate the PDF (survival function times hazard function) of ages-at-death in a birth cohort subject to the hazard function at each age. I'd like to combine these two density

Hi all, I was trying to test the assumption of proportional hazards assumption, I used the cox.zph function >cox.zph(coxfit6) Results are: rho chisq p x1 -0.0396 1.397 2.37e-01 x2 0.1107 9.715 1.83e-03 x3 -0.0885 7.743 5.39e-03 x4 0.0366 1.092 2.96e-01 x5 0.0242 0.455 5.00e-01 GLOBAL

> ... interactions between covariables and time. A model such as "coxph(Surv(ptime, pstat) ~ age + age*ptime, ...." is invalid -- it is not at all what you think. If cph flags this as an error that is a good thing: I should probably add the same message to coxph. > Is is somewhat sensible to use cox.zph() to investigate which variables need time interaction... The cox.zph

Dear List: I have a data frame prepared in the couting process style for including a binary time-dependent covariate. The first few rows look like this. PtNo Start End Status Imp 1 1 0 608.0 0 0 2 2 0 513.0 0 0 3 2 513 887.0 0 1 4 3 0 57.0 0 0 5 3 57 604.0 0 1 6 4 0 150.0 1 0 The outcome

Hello, Excuse me for a more methodological than technical question. I'm developing a Cox model with 10 covariates. One of them is age (named "eta"). I've checked proportionality with cox.zph with age continuous: > cox.zph(coxph(Surv(TTP,CENSOTTP)~eta)) rho chisq p eta -0.0154 0.0225 0.88 and categorical (eta<60): >

Hi, I am trying to convert the following NLMIXED code to NLME, but am running into problems concerning 'Singularity in backsolve'. As I am new to R/S-Plus, I thought I may be missing something in the NLME code. NLMIXED *********** proc nlmixed data=kidney.kidney; parms delta=0.03 gamma=1.1 b1=-0.003 b2=-1.2 b3=0.09 b4=0.35 b5=-1.43 varu=0.5; eta=b1*age+b2*sex+b3*gn+b4*an+b5*pkn+u;