search for: fitsurv

...e joint model to longitudinal and survival data. > I have come accross a range of errors when trying different things and > just can't seem to get around them all. > > The code I use is as follows: > fitLME = lme(cd4~trt+time, random=~time|num, data=mnuts2); summary(fitLME) > fitSURV = coxph(Surv(fail.time, SI.code)~trt, x=TRUE, data=cov); > summary(fitSURV) > fitJM = jointModel(fitLME, fitSURV, timeVar="time", > method="piecewise-PH-GH"); summary(fitJM) > > Both the lme and coxph functions work fine and both give the same sample > size (t...

Hi all: I am a user of "JM" package. Here's the problem of "sample size". The warning is: Error in jointModel(fitLME, fitSURV_death, timeVar = "time", method = "piecewise-PH-GH") : sample sizes in the longitudinal and event processes differ. According to the suggestion of "missing data",I use the same data set(data_JM) without any missing value. fitLME <- lme(CD4 ~ time + time:Group...

...the survey design method works in R. I currently have a data set that utilized a complex survey design. The only thing is that only the weight is provided. Thus, I constructed my survey design as: svdes<-svydesign(id=~1, weights=~weightvar, data=dataset) Then, I want to run an OLS model, so: fitsurv<-svyglm(y~x1+x2+x3...xk, design=svdes, data=dataset) But, I want to check if there is evidence of heteroskedasticity. If so, how would I correct the standard errors? Can the "sandwich" library do this? Are the standard errors already adjusted. How else can I verify if heteroskedastici...