Last chance! 50% off unlimited learning
Sale ends in
Calculates the characteristics of a design and returns it.
getDesignCharacteristics(design)The trial design.
Returns a TrialDesignCharacteristics object.
The following generics (R generic functions) are available for this result object:
names to obtain the field names,
print to print the object,
summary to display a summary of the object,
plot to plot the object,
as.data.frame to coerce the object to a data.frame,
Click on the link of a generic in the list above to go directly to the help documentation of
the rpact specific implementation of the generic.
Note that you can use the R function methods to get all the methods of a generic and
to identify the object specific name of it, e.g.,
use methods("plot") to get all the methods for the plot generic.
There you can find, e.g., plot.AnalysisResults and
obtain the specific help documentation linked above by typing ?plot.AnalysisResults.
Calculates the inflation factor (IF), the expected reduction in sample size under H1, under H0, and under a value in between H0 and H1. Furthermore, absolute information values are calculated under the prototype case testing H0: mu = 0 against H1: mu = 1.
Other design functions:
getDesignConditionalDunnett(),
getDesignFisher(),
getDesignGroupSequential(),
getDesignInverseNormal(),
getPowerAndAverageSampleNumber()
# NOT RUN {
# Calculate design characteristics for a three-stage O'Brien & Fleming
# design at power 90% and compare it with Pocock's design.
getDesignCharacteristics(getDesignGroupSequential(beta = 0.1))
getDesignCharacteristics(getDesignGroupSequential(beta = 0.1, typeOfDesign = "P"))
# }
Run the code above in your browser using DataLab