Description Usage Arguments Value See Also Examples

Takes the output from the `completeTrial.pooledArms`

function and generates a plot describing characteristics of the estimated distribution of the treatment arm-pooled number of endpoints.

1 2 3 4 |

`eventTimeFrame` |
a time frame within which endpoints are counted, specified in weeks as |

`eventPPcohort` |
a logical value. If |

`target` |
a vector of target numbers of endpoints for reporting of the estimated probability that the total number of endpoints will be |

`power.axis` |
a logical value. If |

`power.TE` |
a numeric value of treatment efficacy for which power is shown on the top axis. If |

`eventPriorRate` |
a numeric value of the treatment arm-pooled prior mean incidence rate for the endpoint, expressed as the number of events per person-year at risk |

`eventPriorWeight` |
a numeric vector in which each value represents a weight (i.e., a separate scenario) assigned to the prior gamma distribution of the treatment arm-pooled event rate at the time when 50% of the estimated total person-time at risk has been accumulated |

`xlim` |
a numeric vector of the form |

`xlab` |
a character string for the user-specified x-axis label. If |

`ylab` |
a character string for the user-specified y-axis label. If |

`power.lab` |
a character string for the user-specified power-axis label. If |

`xPosLegend` |
a numeric value in |

`fileDir` |
a character string specifying a path for the input directory |

None. The function is called solely for plot generation.

`completeTrial.pooledArms`

and `plotRCDF.byArm`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
arm <- rep(c("C3","T1","T2"), each=250)
schedule <- rbinom(length(arm), 1, 0.01)
entry <- rpois(length(arm), lambda=60)
entry <- entry - min(entry)
last_visit_dt <- entry + runif(length(arm), min=0, max=80)
event <- rbinom(length(arm), 1, 0.01)
dropout <- rbinom(length(arm), 1, 0.02)
dropout[event==1] <- 0
exit <- rep(NA, length(arm))
exit[event==1] <- last_visit_dt[event==1] + 5
exit[dropout==1] <- last_visit_dt[dropout==1] + 5
followup <- ifelse(event==1 | dropout==1, 0, 1)
interimData <- data.frame(arm=arm, schedule2=schedule, entry=entry, exit=exit,
last_visit_dt=last_visit_dt, event=event, dropout=dropout, complete=0,
followup=followup)
weights <- c(0.2, 0.4, 0.6)
for (j in 1:length(weights)){
completeTrial.pooledArms(interimData=interimData, nTrials=50, N=1500, enrollRatePeriod=24,
eventPriorWeight=weights[j], eventPriorRate=0.06, fuTime=80, visitSchedule=seq(0, 80, by=4),
visitSchedule2=c(0,seq(from=8,to=80,by=12)), saveDir="./", randomSeed=9)
}
pdf(file=paste0("./","rcdf_pooled_eventPriorRate=",0.06,".pdf"), width=6, height=5)
plotRCDF.pooledArms(target=c(60,30), power.axis=FALSE, eventPriorRate=0.06,
eventPriorWeight=weights, fileDir="./")
dev.off()
``` |

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