print.TwoSampleAalenJohansen | R Documentation |
Print function for object of class 'TwoSampleAalenJohansen'
## S3 method for class 'TwoSampleAalenJohansen'
print(x, digits = 4, what = "both", method = NULL, absRisk = TRUE, ...)
x |
an object of class 'TwoSampleAalenJohansen' |
digits |
number of digits to print the results |
what |
either "RR", "Diff" or "both" (default), depending on whether we want to print the results for the risk ratio (RR), the risk difference (Diff) or both. |
method |
either "EL", "Wald" or "both", depending on whether we want to print the results obtained when using empirical likelihood inference (EL), Wald-type inference (Wald) or both. Default is 'NULL', which means that 'method' inherits the value of the corresponding control parameter used when creating the object 'x'. |
absRisk |
Default is TRUE and this should not be changed. |
... |
Not used |
no return value, called for printing only.
Paul Blanche
## A simple example for Wald-type inference, using simulated data.
## It illustrates the possible inconsistency of Wald-type inference, in
## terms of statistical significance, when inference is based on the risk
## ratio and on the risk difference. This inconsistency cannot exist
## using an empirical likelihood approach.
ResSimA100 <- TwoSampleAalenJohansen(time=SimA100$time,
cause=SimA100$status,
group=SimA100$group,
t=1,
contr=list(method="Wald"))
print(ResSimA100, digits=3, what="Diff")
print(ResSimA100, digits=3, what="RR")
## Same example data, but now analyzed with and empirical likelihood approach. It
## takes approx 20 seconds to run.
ResSimA100 <- TwoSampleAalenJohansen(time=SimA100$time,
cause=SimA100$status,
group=SimA100$group,
t=1)
print(ResSimA100, digits=3, what="Diff", method="EL")
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