Description Usage Arguments Details Value Examples

Produce the Weighted Kaplan-Meier test statistic. Test statistic is constructed based on the paper of Pepe and Fleming (1989). Coding is based on work from a non-proportional hazards working group at Merck; original author ??

1 |

`survival` |
time-to-event variable |

`cnsr` |
censoring variable: 1=censoring, 0=event |

`trt` |
treatment varaible. Accepted values are either "experiment" or "control" |

`stra` |
stratification variable. Default is |

`fparam` |
parameter description. Set to |

Although it is of interest that the statistic will reduce to RMST when the weight function = 1, the stability conditions proposed by Pepe and Fleming (1989) rule out a constant weight function when censoring is present. Input: dataframe 'indata' contains the following variables: Event.T -> Event time (failure/censor); Status -> 0 = Censored, 1 = Event of Interest; Z -> 0 = Control, 1 = Active

Code returns the Z statistic and p-value.

- pval
One-sided p-Value from weighted Kaplan-Meier test

- z
test statistics

- Df
degree of freedom. Currently always set to

`NA`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
# weighted Kaplan-Meier test on the simulated data
library(survival)
medC = 6
hr <- c(1, 0.6)
intervals <- 3
gamma <- c(2.5, 5, 7.5, 10) ## a ramp-up enrollment
R <- c(2 , 2, 2 , 6 ) ## enrollment period: total of 12 months
eta <- -log(0.99) ## 1% monthly dropout rate
sim1 <- nphsim(nsim=1,lambdaC=log(2)/medC,lambdaE=log(2)/medC*hr, ssC=300,ssE=300,
intervals=intervals,gamma=gamma, R=R,eta=eta)
test1 <- simtest(x=sim1, anaD=c(250,300), method=wkm.Stat)
test1$result[]
# direct function call (without cutoff)
wkm.Stat(surv=sim1$simd$survival, cnsr=sim1$simd$cnsr, trt=sim1$simd$treatment)
``` |

keaven/nphsim documentation built on July 2, 2018, 1:10 a.m.

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