WC.fit {newTestSurvRec}

Survival function estimator for recurrence time data using the estimator developed by Wang and Chang

Description

Estimation of survival function for correlated by the product limit estimator PLE method developed by Wang and Chang.

Usage

WC.fit(x, tvals)

Arguments

x

a survival recurrent event object

tvals

vector of times where the survival function can be estimated.

Details

Wang-Chang (1999) proposed an estimator of the common marginal survivor function in the case where within-unit inter-occurrence times are correlated. The correlation structure considered by Wang and Chang (1999) is quite general and contains, in particular, both the i.i.d. and multiplicative (hence gamma) frailty model as special cases. This estimator removes the bias noted for the product-limit estimator developed by Pena, Strawderman and Hollander (PSH, 2001) when inter-occurrence times are correlated within units. However, when applied to i.i.d. inter-occurrence times, this estimator is not expected to perform as well as the PSH estimator, especially with regard to efficiency.

Value

Value returned

n

number of unit or subjects observed.

m

vector of number of recurrences in each subject (length n)

failed

vector of number of recurrences in each subject (length n*m). Vector ordered (e.g. times of first unit, times of second unit, ..., times of n-unit)

censored

vector of times of censorship for each subject (length n)

numdistinct

number of distinct failures times.

distinct

vector of distinct failures times.

AtRisk

matrix of number of persons-at-risk at each distinct time and for each subject

survfunc

vector of survival estimated in distinct times

tvals

copy of argument.

Note

This function was originally performed by the survrec package, which solved the adjustment problem of the WC estimator using Fortran routines. With the permission of its author, the algorithm was taken, modified, the algorithm, WC estimator was reprogrammed and adapted to the needs of the newTestSurvRec package and thus avoid dependence.

Author(s)

Dr. Carlos M. Martinez M., <[e-mail]>

References

Wang, M. C. and Chang, S.H. (1999). Nonparametric Estimation of a Recurrent Survival Function. J. Amer. Statist. Assoc. 94, 146-153.// Pena E., Strawderman R., Hollander M. (2001). Nonparametric Estimation with Recurrent Event Data. J.A.S.A. 96, 1299-1315.

See Also

PSH.fit, Plot.Event.Rec, Plot.Surv.Rec, Print.Summary

Examples

XL<-data(MMC.TestSurvRec)
#-------------------------------------------------------------------------------------
fitPSHa<-PSH.fit(Survrecu(MMC.TestSurvRec$id,MMC.TestSurvRec$time,
                        MMC.TestSurvRec$event))
fitPSHa$surv
fitPSHa$time
plot(fitPSHa$time,fitPSHa$survfunc,type="s" ,ylim=c(0,1),
        xlim=c(0,max(fitPSHa$time)))
title(main = list("Survival Curve with Recurrent Event Data", 
        cex = 0.8, font = 2.3, col = "dark blue"))
mtext("Research Group: AVANCE USE R!", cex = 0.7, font = 2, 
        col = "dark blue", line = 1)
mtext("Software made by: Dr. Carlos Martinez", cex = 0.6, font = 2, 
        col = "dark red", line = 0)


fitWCa<-WC.fit(Survrecu(MMC.TestSurvRec$id,MMC.TestSurvRec$time,
                        MMC.TestSurvRec$event))
fitWCa$surv
fitWCa$time
plot(fitWCa$time,fitWCa$survfunc,type="s" ,ylim=c(0,1),
        xlim=c(0,max(fitWCa$time)))