Dear AllI am new to R, ?I am struggling to figure out and resolve warning.I have fitted a joint model for survival and longitudinal data using the "JM" library using the syntax below. # Longitudinal submodellmeFit.p1_constr <- lme(sqrtcd4wk ~ cd4tpt ?+ pred:cd4tpt, data = cd4long_constr,? ? ? ? ? ? ? ? ? random = ~cd4tpt|id1, na.action = na.omit)? # Survival submodel for constrictionsurvFit.p1Constr <- coxph(Surv(surv6mon_constr, var6mon_constr) ~ pred, data = surv_full_constr, x = TRUE) # Joint model for constrictionjointFit.p1Constr <- jointModel(lmeFit.p1_constr, survFit.p1Constr, timeVar = "cd4tpt",? ? ? ? ? ? ? ? ? ? ? ? ? method = "piecewise-PH-aGH")summary(jointFit.p1Constr) I am able to get my desired results i.e. estimates and 95% C.I.?I am however not able to calculate ?Martingale residuals from the event process submodel using the following syntax despite being able to calculate Cox-Snell residuals using the following syntax resMartT <- residuals(jointFit.p1Constr, process = "Event", type = "Martingale") #resMartT<-resid(survFit.p1Constr,type='martingale')fitSubY <- fitted(jointFit.p1Constr, process = "Longitudinal", type = "EventTime")plot(fitSubY, resMartT, xlab = "Fitted Values", ylab = "Residuals",main = "Martingale Residuals vs Fitted Values") I get a warning : Warning message: In events - fits : ?longer object length is not a multiple of shorter object length # Cox-Snell residualsresCST <- residuals(jointFit.p1Constr, process = "Event", type = "CoxSnell") sfit <- survfit(Surv(resCST, var6mon_constr) ~ 1, data = surv_full_constr)plot(sfit, mark.time = FALSE, conf.int = TRUE, lty = 1:2, xlab = "Cox-Snell Residuals", ylab = "Survival Probability",?? ? ?main = "Survival Function of Cox-Snell Residuals")curve(exp(-x), from = 0, to = max(surv_full_constr$var6mon_constr), add = TRUE, col = "red", lwd = 2) I will appreciate any assistance rendered ThanksIsaac
Martingale residuals warning
2 messages · Isaac Singini, David Winsemius
On Aug 3, 2016, at 12:07 PM, Isaac Singini via R-help <r-help at r-project.org> wrote: Dear AllI am new to R, I am struggling to figure out and resolve warning.I have fitted a joint model for survival and longitudinal data using the "JM" library using the syntax below. # Longitudinal submodellmeFit.p1_constr <- lme(sqrtcd4wk ~ cd4tpt + pred:cd4tpt, data = cd4long_constr, random = ~cd4tpt|id1, na.action = na.omit) # Survival submodel for constrictionsurvFit.p1Constr <- coxph(Surv(surv6mon_constr, var6mon_constr) ~ pred, data = surv_full_constr, x = TRUE) # Joint model for constrictionjointFit.p1Constr <- jointModel(lmeFit.p1_constr, survFit.p1Constr, timeVar = "cd4tpt", method = "piecewise-PH-aGH")summary(jointFit.p1Constr) I am able to get my desired results i.e. estimates and 95% C.I. I am however not able to calculate Martingale residuals from the event process submodel using the following syntax despite being able to calculate Cox-Snell residuals using the following syntax resMartT <- residuals(jointFit.p1Constr, process = "Event", type = "Martingale") #resMartT<-resid(survFit.p1Constr,type='martingale')fitSubY <- fitted(jointFit.p1Constr, process = "Longitudinal", type = "EventTime")plot(fitSubY, resMartT, xlab = "Fitted Values", ylab = "Residuals",main = "Martingale Residuals vs Fitted Values") I get a warning : Warning message: In events - fits : longer object length is not a multiple of shorter object length # Cox-Snell residualsresCST <- residuals(jointFit.p1Constr, process = "Event", type = "CoxSnell") sfit <- survfit(Surv(resCST, var6mon_constr) ~ 1, data = surv_full_constr)plot(sfit, mark.time = FALSE, conf.int = TRUE, lty = 1:2, xlab = "Cox-Snell Residuals", ylab = "Survival Probability", main = "Survival Function of Cox-Snell Residuals")curve(exp(-x), from = 0, to = max(surv_full_constr$var6mon_constr), add = TRUE, col = "red", lwd = 2) I will appreciate any assistance rendered
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ThanksIsaac [[alternative HTML version deleted]]
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David Winsemius Alameda, CA, USA