Either "ttest" or "ztest" - the test
statistic for the inferences to be based on. Use "ztest" for
binary data applications.
method
The calculation method - use "bootstrap" for a
resampling-based approach and "hung" for calculations using the multivariate normal distribution.
nboot
The number of bootstrap iterations to use.
simerror
Prespecified simulation standard error.
...
Any further arguments.
Details
When handling with data from factorial clinical trial designs, one
is often interested in the question whether dose combinations in the trial
have got a better effect than all of their component drugs, because
regulatoric requirements demand a contribution to the efficacy by all components. The decision if any of the tested combination drugs has
got this property can be based on the AVE- or MAX-statistics
proposed by Hung, Chi and Lipicky (1993). The hypothesis that this is true for
none of the combinations is rejected if the largest or the average of
the min-statistics is sufficiently high. The functions
avetest and maxtest calculate the corresponding p-values
on carpet or cube objects with a new bootstrap
algorithm, which is default, or by the
multivariate method for unbalanced designs from Hung (2000). A
resampling-based method is available also for binary data
applications. The desired simulation accuracy always needs to be specified by the
number nboot of simulations to perform or an upper bound
simerror for the simulation standard error. If both are
given, the two constraints will be held simultaneously. Depending on the type of data, the calculations
can be based on Student's t-test for metric data or the
Z-statistic for binary applications.
Value
An object of class avetest or maxtext, respectively, with the
following slots. The slot name is available for the MAX-test only.
p
p-value for the AVE- or MAX-test.
stat
Observed AVE- or MAX-statistic.
test
Type of test statistic which the AVE- or MAX-test was based on.
method
Algorithm used for the calculation.
nboot
Total number of resampling iterations.
simerror
Simulation standard error.
name
Combination group where the maximum of the min-statistics
was observed.
duration
Total computing duration in seconds.
call
The function call.
Note
The performance of the bootstrap-based approach and the method from Hung
(2000) has been compared and discussed. All algorithms perform very
conservative if the means in the marginal treatment groups are close
for the combinations.