plot.calc_decision_rules: Plot method for 'calc_decision_rules' objects

In ppseq: Design Clinical Trials using Sequential Predictive Probability Monitoring

Plot method for calc_decision_rules objects

Description

Returns a plot of decision rules from the results of calc_decision_rules that can interactively show when to stop and when to proceed at the various interim analyses

Usage

## S3 method for class 'calc_decision_rules'
plot(x, plotly = TRUE, ...)

Arguments

x	an object of class 'calc_decision_rules', usually returned by the calc_decision_rules function
plotly	should the plot be rendered in plotly? (Default is TRUE)
...	unused

Value

In the one-sample case, a heatmap plot with number enrolled on the x-axis and number of responses on the y-axis. In the two-sample case, a grid of heatmap plots. Each plot is a combination of the number enrolled so far in the experimental and control arms. The x-axis is the number of responses in the control arm and the y-axis is the number of responses in the experimental arm. Green indicates combinations where the trial would proceed and red indicates combinations where the trial would stop.

Examples

set.seed(123)

# Two-sample case
dec_tbl <- calc_decision_rules(
  n = cbind(seq(5, 15, 5), seq(5, 15, 5)),
  N = c(15, 15),
  theta = 0.86,
  ppp = 0.2,
  p0 = NULL,
  direction = "greater",
  delta = 0,
  S = 50
)

plot(dec_tbl, plotly = FALSE)

ppseq documentation built on Sept. 11, 2024, 5:20 p.m.