des_two_stage: Design a two-stage two-arm randomised clinical trial assuming...
In ph2rand: Randomized Phase II Oncology Trials with Bernoulli Outcomes

Description Usage Arguments Value See Also Examples

des_two_stage determines two-stage two-arm randomised clinical trial designs, assuming the primary outcome variable is Bernoulli distributed. It supports a flexible framework for specifying which scenarios to control the type-I and type-II error-rates for, and allows for design determination assuming a variety of test statistics. In all instances, des_two_stage computes the optimal required sample size in each arm in each stage, the associated optimal stopping boundaries, and returns information on key operating characteristics.

des_two_stage(
  type = "binomial",
  alpha = 0.1,
  beta = 0.2,
  delta = 0.2,
  ratio = 1,
  Pi0 = 0.1,
  Pi1 = Pi0[1],
  nCmax = 50L,
  equal = T,
  w = c(1, 0, 0, 0, 0),
  piO = Pi0[1],
  efficacy = FALSE,
  futility = TRUE,
  efficacy_type = 0L,
  efficacy_param = NULL,
  futility_type = 1L,
  futility_param = 0L,
  summary = FALSE
)

`type`	A `character` string indicating the chosen design framework/test statistic to assume. Must be one of `"barnard"`, `"binomial"`, `"fisher"`, or `"sat"`. Defaults to `"binomial"`.
`alpha`	A `numeric` indicating the chosen value for α, the significance level (i.e., the type-I error-rate). Defaults to `0.1`.
`beta`	A `numeric` indicating the chosen value for β, used in the definition of the desired power (i.e., the type-II error-rate). Defaults to `0.2`.
`delta`	A `numeric` indicating the chosen value for δ, the treatment effect assumed in the power calculation. Defaults to `0.2`.
`ratio`	A `numeric` indicating the chosen value for r, the allocation ratio to the experimental arm, relative to the control arm. Defaults to `1`.
`Pi0`	A `numeric` `vector` indicating the chosen values of the control arm response rate to control the type-I error-rate to level α for. Must either be of `length` one, indicating a single point, or of `length` two. In this case, the elements indicate the range of possible response rates to allow for. Defaults to `0.1`.
`Pi1`	A `numeric` `vector` indicating the chosen values of the control arm response rate to allow for in the power calculations. Must either be of `length` one, indicating a single point, or of `length` two. In this case, the elements indicate the range of possible response rates to allow for. Defaults to `Pi0[1]`.
`nCmax`	A `numeric` indicating the maximum value of the sample size in the control arm (across both stages) to consider in the search procedure. Defaults to `50L`.
`equal`	A `logical` variable indicating whether the sample size of the two stages should be equal. Defaults to `TRUE`.
`w`	A `numeric` `vector` indicating the weights to use in the optimality criteria. Must be of `length` five, with all elements greater than or equal to zero, and at least one of the first four elements strictly positive. Defaults to `c(1, 0, 0, 0, 0)`.
`piO`	A `numeric` indicating the value of the control arm response rate to assume in the optimality criteria. Defaults to `Pi0[1]`.
`efficacy`	Only used if `type` is one of `"barnard"`, `"binomial"`, or `"sat"`. Then, it is a `logical` variable indicating whether to include early stopping for efficacy in the design. Defaults to `FALSE`.
`futility`	Only used if `type` is one of `"barnard"`, `"binomial"`, or `"sat"`. Then, it is a `logical` variable indicating whether to include early stopping for futility in the design. Defaults to `TRUE`.
`efficacy_type`	Only used if `type` is `"fisher"`. Then, it is a `numeric` indicating whether, and which type of, early stopping for efficacy to include in the design. See the vignette for details. Defaults to `0L`.
`efficacy_param`	Only used if `type` is `"fisher"` and `efficacy_type` is not equal to `0L`. Then, it is a `numeric` that influences the precise way in which an efficacy boundary is specified. See the vignette for details. Defaults to `NULL`.
`futility_type`	Only used if `type` is `"fisher"`. Then, it is a `numeric` indicating whether, and which type of, early stopping for futility to include in the design. See the vignette for details. Defaults to `1L`.
`futility_param`	Only used if `type` is `"fisher"` and `futility_type` is not equal to `0L`. Then, it is a `numeric` that influences the precise way in which a futility boundary is specified. See the vignette for details. Defaults to `1L`.
`summary`	A `logical` variable indicating whether a summary of the function's progress should be printed to the console. Defaults to `FALSE`.

A list with additional class "ph2rand_des", containing each of the input parameters along with several additional variables, including

A list in the slot $boundaries giving the rejection boundaries of the optimal design. The names of these elements depends on the value of type.
A tibble in the slot $feasible summarising the operating characteristics of the feasible designs.
A numeric vector in the slot $nC giving the sample sizes in the control arm in each stage for the optimal design.
A numeric vector in the slot $nE giving the sample sizes in the experimental arm in each stage for the optimal design.
A tibble in the slot $opchar summarising the operating characteristics of the optimal design.

des_one_stage, opchar, pmf, terminal, plot.ph2rand_des, summary.ph2rand_des.

# The design for the default parameters
des       <- des_two_stage()
# Controlling the type-I/II error-rates over a range of possible response
# rates
des_range <- des_two_stage(Pi0 = c(0, 1),
                           Pi1 = c(0, 0.8))