- design
The trial design. If no trial design is specified, a fixed sample size design is used.
In this case, Type I error rate alpha, Type II error rate beta, twoSidedPower,
and sided can be directly entered as argument where necessary.
- ...
Ensures that all arguments (starting from the "...") are to be named and
that a warning will be displayed if unknown arguments are passed.
- groups
The number of treatment groups (1 or 2), default is 2.
- normalApproximation
The type of computation of the p-values. Default is FALSE for
testing means (i.e., the t test is used) and TRUE for testing rates and the hazard ratio.
For testing rates, if normalApproximation = FALSE is specified, the binomial test
(one sample) or the exact test of Fisher (two samples) is used for calculating the p-values.
In the survival setting normalApproximation = FALSE has no effect.
- riskRatio
If TRUE, the design characteristics for
one-sided testing of H0: pi1 / pi2 = thetaH0 are simulated, default is FALSE.
- thetaH0
The null hypothesis value,
default is 0 for the normal and the binary case (testing means and rates, respectively),
it is 1 for the survival case (testing the hazard ratio).
For non-inferiority designs, thetaH0 is the non-inferiority bound.
That is, in case of (one-sided) testing of
means: a value != 0
(or a value != 1 for testing the mean ratio) can be specified.
rates: a value != 0
(or a value != 1 for testing the risk ratio pi1 / pi2) can be specified.
survival data: a bound for testing H0: hazard ratio = thetaH0 != 1 can be specified.
For testing a rate in one sample, a value thetaH0 in (0, 1) has to be specified for
defining the null hypothesis H0: pi = thetaH0.
- pi1
A numeric value or vector that represents the assumed probability in
the active treatment group if two treatment groups
are considered, or the alternative probability for a one treatment group design,
default is seq(0.2, 0.5, 0.1) (power calculations and simulations) or
seq(0.4, 0.6, 0.1) (sample size calculations).
- pi2
A numeric value that represents the assumed probability in the reference group if two treatment
groups are considered, default is 0.2.
- plannedSubjects
plannedSubjects is a vector of length kMax (the number of stages of the design)
that determines the number of cumulated (overall) subjects when the interim stages are planned.
For two treatment arms, it is the number of subjects for both treatment arms.
For multi-arm designs, plannedSubjects refers to the number of subjects per selected active arm.
- directionUpper
Specifies the direction of the alternative,
only applicable for one-sided testing; default is TRUE
which means that larger values of the test statistics yield smaller p-values.
- allocationRatioPlanned
The planned allocation ratio n1 / n2 for a two treatment groups
design, default is 1. For multi-arm designs, it is the allocation ratio relating the active arm(s) to the control.
- minNumberOfSubjectsPerStage
When performing a data driven sample size recalculation,
the vector minNumberOfSubjectsPerStage with length kMax determines the
minimum number of subjects per stage (i.e., not cumulated), the first element
is not taken into account. For two treatment arms, it is the number of subjects for both treatment arms.
For multi-arm designs minNumberOfSubjectsPerStage refers
to the minimum number of subjects per selected active arm.
- maxNumberOfSubjectsPerStage
When performing a data driven sample size recalculation,
the vector maxNumberOfSubjectsPerStage with length kMax determines the maximum number
of subjects per stage (i.e., not cumulated), the first element is not taken into account.
For two treatment arms, it is the number of subjects for both treatment arms.
For multi-arm designs maxNumberOfSubjectsPerStage refers
to the maximum number of subjects per selected active arm.
- conditionalPower
If conditionalPower together with minNumberOfSubjectsPerStage and
maxNumberOfSubjectsPerStage (or minNumberOfEventsPerStage and maxNumberOfEventsPerStage
for survival designs) is specified, a sample size recalculation based on the specified conditional power is performed.
It is defined as the power for the subsequent stage given the current data. By default,
the conditional power will be calculated under the observed effect size. Optionally, you can also specify thetaH1 and
stDevH1 (for simulating means), pi1H1 and pi2H1 (for simulating rates), or thetaH1 (for simulating
hazard ratios) as parameters under which it is calculated and the sample size recalculation is performed.
- pi1H1
If specified, the assumed probability in the active treatment group if two treatment groups
are considered, or the assumed probability for a one treatment group design, for which the conditional
power was calculated.
- pi2H1
If specified, the assumed probability in the reference group if two treatment groups
are considered, for which the conditional power was calculated.
- maxNumberOfIterations
The number of simulation iterations, default is 1000.
- seed
The seed to reproduce the simulation, default is a random seed.
- calcSubjectsFunction
Optionally, a function can be entered that defines the way of performing the sample size
recalculation. By default, sample size recalculation is performed with conditional power with specified
minNumberOfSubjectsPerStage and maxNumberOfSubjectsPerStage (see details and examples).
- showStatistics
If TRUE, summary statistics of the simulated data
are displayed for the print command, otherwise the output is suppressed, default
is FALSE.