Description Usage Arguments Value Author(s) References See Also Examples
View source: R/Plot.Event.Rec.R
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).
1 | Plot.Event.Rec(yy, xy, xf)
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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. |
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.
Dr. Carlos Mart<ed>nez <cmmm7031@gmail.com>
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.
Dif.Surv.Rec
1 2 3 4 5 | data(TBCplapyr)
# See, the unit number 14
Plot.Event.Rec(TBCplapyr,14,14)
# See, the unit number 5
Plot.Event.Rec(TBCplapyr,5,5)
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