OneSampleNormal1.Design {BayesDIP}

One sample Normal model with one-parameter unknown, given variance

Description

#' Calculate the minimum planned sample size under an admissible design. The users decide the power and type-I-error, and pick the efficacy and futility boundaries. If there are no admissible design based on controlled type-I-error, then default to output the designs with the lowest type-I-error and at least the user-defined (e.g. 80%) power.

Usage

OneSampleNormal1.Design(
  prior,
  nmin = 10,
  nmax = 100,
  mu0,
  mu1,
  var,
  d = 0,
  ps,
  pf,
  power = 0.8,
  t1error = 0.05,
  alternative = c("less", "greater"),
  seed = 202209,
  sim = 1000
)

Arguments

prior

A list of length 2 containing the distributional information of the prior. The first element is a number specifying the type of prior. Options are

1. DIP ;

2. Normal(mu0,var/n0), where mu0 = prior mean, var = the known variance

The second elements of the list is the parameter n0.

nmin

The start searching sample size

nmax

The stop searching sample size

mu0

The null mean value, which could be taken as the standard or current mean.

mu1

The mean value of the new treatment.

var

The variance

d

The target improvement (minimal clinically meaningful difference).

ps

The efficacy boundary (upper boundary).

pf

The futility boundary (lower boundary).

power

The power to achieve.

t1error

The controlled type-I-error.

alternative

less (lower values imply greater efficacy) or greater (larger values imply greater efficacy).

seed

The seed for simulations.

sim

The number of simulations.

Value

A list of the arguments with method and computed elements.

Examples

# with traditional Bayesian prior Beta(1,1)
OneSampleNormal1.Design(list(2,6), nmin = 10, nmax = 100, mu0 = 100, mu1 = 95, var=15, d = 0.05,
                  ps = 0.95, pf = 0.05, power = 0.8, t1error = 0.05, alternative = "less",
                  seed = 202210, sim = 10)
# with DIP
OneSampleNormal1.Design(list(1,0), nmin = 10, nmax = 100, mu0 = 100, mu1 = 95, var=15, d = 0.05,
                  ps = 0.95, pf = 0.05, power = 0.8, t1error = 0.05, alternative = "less",
                  seed = 202210, sim = 10)