| getDesignCharacteristics {rpact} | R Documentation |
Get Design Characteristics
Description
Calculates the characteristics of a design and returns it.
Usage
getDesignCharacteristics(design = NULL, ...)
Arguments
design |
The trial design. |
... |
Ensures that all arguments (starting from the "...") are to be named and that a warning will be displayed if unknown arguments are passed. |
Details
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.
Value
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 adata.frame, -
as.matrix()to coerce the object to amatrix.
How to get help for generic functions
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.
See Also
Other design functions:
getDesignConditionalDunnett(),
getDesignFisher(),
getDesignGroupSequential(),
getDesignInverseNormal(),
getGroupSequentialProbabilities(),
getPowerAndAverageSampleNumber()
Examples
# 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"))