PSH.fit {newTestSurvRec}

Estimator of the survival curve using the estimator developed by Pena, Strawderman and Hollander

Description

Estimation of survival function for recurrence time data by means the generalized product limit estimator (PLE) method developed by Pena, Strawderman and Hollander. The resulting object of class Survrecu is plotted by plot, before it is returned.

Usage

PSH.fit(x, tvals)

Arguments

x

a survival recurrent event object

tvals

vector of times where the survival function can be estimated.

Details

The estimator computed by this object is the nonparametric estimator of the inter-event time survivor function under the assumption of a renewal or IID model. This generalizes the product-limit estimator to the situation where the event is recurrent. For details and the theory behind this estimator, please refer to Pena, Strawderman and Hollander (2001, JASA).

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 PSH estimator using Fortran routines. With the permission of its author, the algorithm of the packet base was taken, modified, the algorithm of the PSH estimates 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

Pena, E.A., Strawderman, R. and Hollander M. (2001). Nonparametric Estimation with Recurrent Event Data. J. Amer. Statist. Assoc. 96, 1299-1315.// Pena E., Strawderman R., Hollander, M. (2001). Nonparametric Estimation with Recurrent Event Data. J.A.S.A. 96, 1299-1315.

See Also

WC.fit, Survrecu, Plot.Event.Rec, Plot.Surv.Rec, Print.Summary

Examples

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)