similar to: non parametric estimates of the hazard with right censored data

Hello, If all I have access to is an empirically calculated hazard function, is it possible to compute an approximate value for the mean lifetime? I know that if the hazard function is essentially constant, the mean lifetime is 1/hazard rate. ?But if I'm confident that the empirical hazard function is not constant, I'm not sure how to go about calculating an estimate of mean lifetime.

Dear All, I would like to ask if it is possible to estimate a hazard function using the muhaz command when all the data is right-censored. My data has information of the number of weeks people has been unemployed but all of them are unemployed at the date of the survey, that is, I cannot observed when the individuals leave the unemployment state. I appreciate your help, Best, Monica L.

Hello, Is it possible to create confidence intervals for hazard rates? ?I'm creating two muhaz objects:? haz1 <- muhaz(NumDaysCustomer[cRV=="true"],status[cRV=="true"]) haz2 <- muhaz(NumDaysCustomer[cRV=="false"],status[cRV=="false"]) and plotting them. ? There are many, many more observations in the cohort cRV=="false" than

Dear R users, I am trying to use "muhaz" and "plot.muhaz" functions in "muhaz" package to estimate and plot hazard funciton. However function "muhaz" always gives error message "Error in Surv(times, delta) : object "times" not found". I could not even run their sample codes in the user's manual as follows: data(ovarian)

Dear colleagues, I have the following dataset. It is modelled on the data included in Box-Seteffenheiser and Jones "Event History Modelling" Using the following code, I try to find the baseline hazard function haz_1<-muhaz(bpa$time, bpa$censored, subset=(bpa$year=="2010" | bpa$ban=="1"), min.time=1, max.time=3) I think I'm doing everything right, but what I

Hello. ?I am hoping someone will be willing to help me understand something about hazard plots created with muhaz(...). ?I have some background in statistics (minor in grad school), but I haven't been able to figure one thing about hazard plots. ?I am using hazard plots to track customer cancellations. ?I figure I can treat a cancellation as a "death", and if someone is still a

Dear all, I am using Windows and R 2.9.2 for my analyses. I have a large dataset and I am particularly interested in looking at time to an event for a continuous variable. I would like to produce a plot of log(relative risk) or relative risk (also known as hazard ratio) against the continuous variable. I have spent a long time looking for advice on how to do this but my search has proved

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

Hello, I would like to use the parfm package: https://cran.r-project.org/web/packages/parfm/parfm.pdfhttps://cran.r-project.org/web/packages/parfm/parfm.pdf in my work. This package fits parametric frailty models to survival data. To ensure I was using it properly, I started by running some small simulations to generate some survival data (without any random effects), and analyse the data using

Dear maintainers and R-devel, Several orphaned CRAN packages are about to be archived due to outstanding QC problems, but have CRAN and BioC packages depending on them which would be broken by the archival (and hence need archiving alongside). Therefore we are looking for new maintainers taking over maintainership for one or more of the following packages: R2HTML SemiPar cghseg hexbin lgtdl

Dear R-colleagues, Is it possible to mix TEXT and VALUE of objects in y (or x) label of a plot? For instance: f<-2 plot(..., ylab='Axis f', ...) where "f" means the VALUE of "f". Thany you in advance, Eric. -- Barba Departamento de Ciências Exatas Universidade Federal de Lavras Minas Gerais - Brasil [[alternative HTML version deleted]]

Hi all! I have two survival data sets looking at similar effects in different settings. One data set is only right censored, but the other is interval censored. In the right censored data set, there is an effect of one factor that causes very different shapes in survival curves (and non-proportional hazards) and I'd really like to say that the same factor has a similar effect in the other

I would like to simulate a stochastic process by specifying an intensity function, say lambda(t)=0.05 + 3 exp(鈭抰) I have the following code, but it has a number of problems. One issue I have is I do not know where the time variable is. I would appreciate your help with this code. library("survival") n <- 5000 lamc<-0.08 k1<-0.05 k2<-3 ld<-function(t){k1+k2}

Hi Forum, i am reading a csv file and running the command censummary for a summary statistics on a censored dataset... the output in the console looks like, but with an errror message in the end :( > censtat <- read.csv("C:/Documents and > Settings/ed/Desktop/Project-Datasets/pyrene.csv", header = TRUE) > censtat Pyrene Cen 1 28 TRUE 2 31 FALSE 3 32

Greetings -- I would like to estimate a proportional hazard model with a weibull or lognormal baseline. I have looked at both the coxph() and survreg() functions and neither appear (to me ) to do it. Am I missing something in the docs or is there another terrific package out there that will do this. Many Thanks. Carl Mason

Hi I have estimated a hazard function using a kernel based method. Now i have to generate a random variate that follows this hazard function. Does any one know method I should use to generate the variate. Thanks Samiul -- View this message in context: http://www.nabble.com/Generate-random-variate-from-a-non-parametric-hazard-function-tp26034880p26034880.html Sent from the R help mailing list

Dear R help I have a question on the variance of the binomial probit model. I have fitted the following model : > lmer1<-lmer(mp ~ l + op + l*op+ us_lev + bw_lev +(1|tatu) , + family = binomial(link="probit"), + method = 'Laplace', + data = matings, + msVerbose= True) > summary(lmer1) Generalized linear

Dear all, I use the package RCOM to manipulate Excel-Files (Windows). After opening the Excel-File and formatting the cells I want to save the file automatically without request. If I use y[["Save"]] <- TRUE it opens the saving dialog and I have to select the destination for saving. But I simply want to overwrite the existing file without any other workings. Thany your very much

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 I am trying to analyse data which is left-censored (i.e. has values below the detection limit). I have been using the NADA package of R to derive summary statistics and do some regression. I am now trying to carry out regression on paired data where both my X and Y have left-censored data within them. I have tried various commands in R: rega = cenreg(Cen(conc, cens_ind) ~ Gp_ident))? with