plot_p {adestr} | R Documentation |
Creates a plot of the p-values and implied rejection boundaries on a grid of values for the first and second-stage test statistics.
plot_p(
estimator,
data_distribution,
design,
mu = 0,
sigma,
boundary_color = "lightgreen",
subdivisions = 100,
...
)
estimator |
object of class |
data_distribution |
object of class |
design |
object of class |
mu |
expected value of the underlying normal distribution. |
sigma |
assumed standard deviation. |
boundary_color |
color of the implied rejection boundary. |
subdivisions |
number of subdivisions per axis for the grid of test statistic values. |
... |
additional arguments handed down to ggplot |
When the first-stage test statistic lies below the futility threshold (c1f) or
above the early efficacy threshold (c1e) of the TwoStageDesign
,
there is no second-stage test statistics. The p-values in these regions are only
based on the first-stage values.
For first-stage test statistic values between c1f and c1e, the first and second-stage
test statistic determine the p-value.
The rejection boundary signals the line where
a ggplot2
object visualizing the p-values on a grid of possible test-statistic values.
plot_p(estimator = StagewiseCombinationFunctionOrderingPValue(),
data_distribution = Normal(FALSE),
design = get_example_design(),
mu = 0,
sigma = 1)