Plot.Event.Rec: This function plots the ocurrence of one recurrent event on...

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/Plot.Event.Rec.R

Description

Recurrent events are plotted. A plot is returned. The counting processes are a powerful tools in survival analysis. These process consider two scale time, a calendar time and a gap time. This idea originally provides from Gill (1981) and the concept was extended by Pe<f1>a et al. (2001).

Usage

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Plot.Event.Rec(yy, xy, xf)

Arguments

yy

Object type recurrent events data. Example: TBCplapyr

xy

Identification of the unit to plotted. xy = 1 is defect value.

xf

Argument to plot the ocurrent events of the unit xf. xf = 1 is defect value.

Value

Plot is returned. Pe<f1>a et al. (2001) designed a special graphic, that allows to count the occurrence of events per unit time. Doubly indexed processes illustration for an case. The graphic shows a case followed during 24.01 months. This patient presents four recurrences at months 7, 10, 16 and 24 from the beginning of study. This fact implies that interoccurrence. times are 7, 3, 6, 8 and the censored time correspond to 0.01 months. Let us assume that we are interested in computing the single processes, N(t) and Y (t) for a selected interoccurrence time t = 5. In this case N(t = 5) = 1 and Y (t = 5) = 3. For the calendar time scale, s = 20, we have N(s = 20) = 3 and Y (s = 20) = 1. Now, let us assume that we would like to know double-indexed processes for both selected interoccurrence and calendar times. Using both time scales we observe that N_{14}(s = 20,t = 5)=1, Y_{14}(s = 20, t = 5) = 2 and Δ\,N_{14}(s = 20,t = 6) = 1.

Author(s)

Dr. Carlos Mart<ed>nez <cmmm7031@gmail.com>

References

Mart<ed>nez C., Ram<ed>rez, G., V<e1>squez M. (2009).Pruebas no param<e9>tricas para comparar curvas de supervivencia de dos grupos que experimentan eventos recurrentes. Propuestas. Revista Ingenier<ed>a U.C.,Vol 16, 3, 45-55. Pe<f1>a E., Strawderman R., Hollander, M. (2001). Nonparametric Estimation with Recurrent Event Data. J.A.S.A. 96, 1299-1315. Gill, R. (1981) Testing with replacement and the product-limit estimator. Ann. Statist., 9, 853-860.

See Also

Dif.Surv.Rec

Examples

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data(TBCplapyr)
 # See, the unit number 14
 Plot.Event.Rec(TBCplapyr,14,14)
 # See, the unit number 5 
 Plot.Event.Rec(TBCplapyr,5,5)

TestSurvRec documentation built on May 29, 2017, 8:27 p.m.