| plot.cpd.PwrGSD {PwrGSD} | R Documentation |
Creates a trellis plot of type II error probability and power at each interim analysis, stacked, versus an effect size variable, conditioned upon levels of up to two factors.
## S3 method for class 'cpd.PwrGSD': plot(x, formula, subset, na.action,...)
x |
an object of class cpd.PwrGSD |
formula |
a one sided formula of the form ~ effect | f1
or ~ effect | f1 * f2 where effect, f1, and
f2 are variables in the indexing dataframe descr, or
the special variable stat which may be used when there are
multiple test statistics per component of Elements. See
the example in the documentation for cpd.PwrGSD |
subset |
the plot can be applied to a subset of rows of
descr via a logical expression on its variables in
combination with the special variable, stat when applicable. |
na.action |
a na.action method for handling NA
values |
... |
other parameters to pass to the R function coplot
usually not neccesary |
Returns the object, x, invisibly
This processes the cpd.PwrGSD object into a dataframe,
stacked on interim looks and then passes the results to the R
function coplot
Abovementioned cpd.PwrGSD processing done by Grant
Izmirlian <izmirlian@nih.gov>
Chambers, J. M. (1992) Data for models. Chapter 3 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.
Cleveland, W. S. (1993) Visualizing Data. New Jersey: Summit Press.
cpd.PwrGSD Power and Elements
## See the example in the 'cpd.PwrGSD' documentation