plot_ep: Plot event prediction output

In gestate: Generalised Survival Trial Assessment Tool Environment

Plot event prediction output

Description

This function plots the output from event_prediction().
By default, produces a plot of predicted events over time, with confidence intervals if available.
Alternatively, produces a plot with the fitting CI over time with same percentage as prediction interval.
By default, both conditional and unconditional trajectories are plotted (if conditional event prediction is available).
Options are available to customise inclusion.

Usage

plot_ep(
  data,
  trajectory = c("both", "conditional", "unconditional"),
  which_PI = c("both", "conditional", "unconditional", "none"),
  prediction_fitting = c("prediction", "fitting"),
  observed = NULL,
  target = NULL,
  max_time = NULL,
  max_E = NULL,
  legend_position = c("top_left", "bottom_right"),
  no_legend = FALSE,
  ...
)

Arguments

data	Full output list from event_prediction().
trajectory	String, choice of "both","conditional","unconditional", for which trajectory to plot. (Default="both")
which_PI	String, choice of "both","conditional","unconditional","none", for which PIs to plot. (Default="both")
prediction_fitting	String, choice of "prediction" or "fitting" (Default = "prediction"). Determines the nature of the intervals; PIs are relevant for prediction of the observation of future trajectories (sample level), whereas fitting CIs concern the interval for the mean trajectory itself (population level).
observed	Optional trajectory of observed event numbers. If vector specified, will plot values at integer times starting from 1. If 2-column matrix specified, will take x-values from column 1 and y-values from column 2. (Default=NULL; not plotted).
target	Optional target number of events to plot. (Default=NULL; not plotted)
max_time	Optional maximum time to plot up to if you do not want to plot full trajectory. (Default=NULL; maximum time determined by input data)
max_E	Optional maximum number of events to plot up to. (Default=NULL; maximum event number is the number of patients)
legend_position	String with any of "top_left", or "bottom_right", corresponding to legend position in power plot. (Default="top_left").
no_legend	Boolean to turn off legend. Default is FALSE; legend shown.
...	Additional graphical parameters.

Value

Returns NULL

Author(s)

James Bell

Examples

recruit <- PieceR(matrix(c(rep(1,12),10,15,25,30,45,60,55,50,65,60,55,30),ncol=2),1)
trial_long <- simulate_trials(active_ecurve=Weibull(50,0.8),control_ecurve=Weibull(50,0.8),
rcurve=recruit,fix_events=200, iterations=1,seed=12345,detailed_output=TRUE)
trial_short <- set_assess_time(data=trial_long,time=10,detailed_output = FALSE)

maxtime <- max(ceiling(trial_long[,"Assess"]))
events <- rep(NA,maxtime)
for (i in 1:maxtime){events[i] <- sum(1-set_assess_time(trial_long,i)[,"Censored"])}

predictions <- event_prediction(data=trial_short, Event="Censored", censoringOne=TRUE, 
type="Weibull", rcurve=recruit, max_time=60, cond_Events=49, cond_NatRisk=451, 
cond_Time=10, units="Months")

plot_ep(predictions,trajectory="conditional",which_PI="conditional",max_time=40,observed=events,
target=200,max_E=200)

plot_ep(predictions,trajectory="unconditional",which_PI="unconditional",max_time=40,
observed=events,target=200,max_E=200)

plot_ep(predictions,trajectory="conditional",which_PI="none",observed=events[1:10],max_time=20,
max_E=150)

gestate documentation built on April 26, 2023, 5:10 p.m.