station.test.plot: Graphical Test of the Stationarity Assumption
In CoxPhLb: Analyzing Right-Censored Length-Biased Data

Description Usage Arguments Details References See Also Examples

Returns a plot of two Kaplan-Meier curves for forward recurrence time and backward recurrence time.

1	station.test.plot(a, v, delta)

`a`	A vector of backward recurrence time (i.e., left-truncation time).
`v`	A vector of forward recurrence time (i.e., failure time minus left-truncation time).
`delta`	A vector of censoring indicator, 0=censored, 1=uncensored.

The stationarity assumption can be checked by comparing the Kaplan-Meier curves. More overlap of the two survival curves suggests stronger evidence of stationarity.

Asgharian, M., Wolfson, D. B., and Zhang, X. (2006). Checking stationarity of the incidence rate using prevalent cohort survival data. Statistics in medicine, 25(10), 1751-1767.

coxphlb, coxphlb.ftest, coxphlb.phtest, station.test

# Check the Stationarity Assumption Graphically
station.test.plot(ExampleData1$a, ExampleData1$y-ExampleData1$a,
                  ExampleData1$delta)			# plot curves

station.test.plot(ExampleData2$a, ExampleData2$y-ExampleData2$a,
                  ExampleData2$delta)			# plot curves