simulate_trial_anova: Simulate trial with ANOVA analysis

In jatotterdell/mfittrial: Functions for MFIT Trial

Simulate trial with ANOVA analysis

Description

Simulate trial with ANOVA analysis

Usage

simulate_trial_anova(
  n_seq = c(107, 214, 320),
  n_delay = 27,
  m_baseline = rep(35, 16),
  m_outcome = rep(35, 16),
  v_bo = diag(8.3^2, 2),
  p_pref = rep(1/4, 4),
  p_alloc = matrix(0.25, 4, 4, dimnames = list(int = 1:4, pref = 1:4)),
  kappa_sup = 0.95,
  kappa_act = (1 - kappa_sup)/3,
  brar = FALSE,
  adjust_baseline = FALSE,
  M0 = rep(0, 16 + adjust_baseline),
  S0 = diag(c(100^2, rep(10, 6), rep(1, 9))),
  A0 = 0.01,
  B0 = 0.01,
  drop_arms = FALSE,
  fix_ctr = NULL,
  verbose = FALSE,
  ...
)

Arguments

n_seq	The sample size at which analysis occurs
n_delay	The number with delayed outcome
m_baseline	The baseline response on ordinal scale
m_outcome	The outcome response on ordinal scale
v_bo	The correlation between baseline and outcome measurement
p_pref	The distribution of preferences in the population
p_alloc	The allocation probability to each arm conditional on preference
kappa_sup	Threshold for superiority
kappa_act	Threshold for remaining active
brar	Use RAR?
adjust_baseline	Include the baseline measurement in the model
M0	Prior mean
S0	Prior variance
A0	Prior scale for variance
B0	Prior shape for variance
drop_arms	Allow dropping of arms?
fix_ctr	Fixed allocation to control
verbose	Be chatty

jatotterdell/mfittrial documentation built on Sept. 30, 2022, 12:23 p.m.