# Design a multi-stage drop-the-losers multi-arm clinical trial for a normally distributed primary outcome

Source: `R/des_dtl_norm.R`
`des_dtl_norm.Rd`

`des_dtl_norm()` determines multi-stage drop-the-losers multi-arm clinical trial designs assuming the primary outcome variable is normally distributed. It computes required design components and returns information on key operating characteristics.

    des_dtl_norm(
      Kv = c(2, 1),
      alpha = 0.025,
      beta = 0.1,
      delta1 = 0.5,
      delta0 = 0,
      sigma = 1,
      ratio = 1,
      power = "marginal",
      type = "variable",
      integer = FALSE,
      summary = FALSE
    )

## Arguments

Kv | A `numeric` `vector` of strictly decreasing values, indicating the chosen value for K, the number of experimental treatment arms present in each stage. Defaults to `c(2, 1)`.
alpha | A `numeric` indicating the chosen value for α, the significance level (family-wise error-rate). Defaults to `0.025`.
beta | A `numeric` indicating the chosen value for β, used in the definition of the desired power. Defaults to `0.1`.
delta1 | A `numeric` indicating the chosen value for δ1, the 'interesting' treatment effect. Defaults to `0.5`.
delta0 | A `numeric` indicating the chosen value for δ0, the 'uninteresting' treatment effect. Defaults to `0`.
sigma | A `numeric` `vector` indicating the chosen values for σ0 and σ1, the standard deviations of the responses in the control and experimental arms. Must be of `length` 1 or 2. If of `length` 1, it is assumed that σ0 =σ1. Defaults to `1`.
ratio | A `numeric` indicating the chosen value for r, the stage-wise allocation ratio to present experimental arms. Defaults to `1`.
power | A `character` string indicating the chosen type of power to design the trial for. Can be `"disjunctive"` or `"marginal"`. Defaults to `"marginal"`.
type | A `character` string indicating the choice for the stage-wise sample size. Can be `"variable"` or `"fixed"`. Defaults to `"variable"`.
integer | A `logical` variable indicating whether the computed possible sample sizes required in each arm in each stage should be forced to be whole numbers. Defaults to `FALSE`. WARNING: If you set `integer = TRUE` and `ratio != 1`, obscure results can occur due to difficulties in identifying a suitable whole number sample size that meets the allocation ratio requirement.
summary | A `logical` variable indicating whether a summary of the function's progress should be printed to the console. Defaults to `FALSE`.

## Value

A `list`, with additional class `"multiarm_des_dtl_norm"`, containing the following elements:

- A `tibble` in the slot `$opchar` summarising the operating characteristics of the identified design.

- A `numeric` in the slot `$e` specifying e, the trial's critical rejection boundary for the final analysis.

- A `numeric` in the slot `$maxN` specifying N, the trial's total required sample size.

- A `numeric` in the slot `$n_factor`, for internal use in other functions.

- A `numeric` in the slot `$n1` specifying n1, the total sample size required in stage one of the trial.

- A `numeric` in the slot `$n10` specifying n10, the sample size required in the control arm in stage one of the trial.

- Each of the input variables.

## See also

`build_dtl_norm`, `gui`, `opchar_dtl_norm`, `plot.multiarm_des_dtl_norm`, `sim_dtl_norm`.

## Examples

    # The design for the default parameters
    des <- des_dtl_norm()