mem_single: Fit the MEM Model for single subgroup

In kaneplusplus/borrow: Borrow Power from Historical Clinical Trials

Description

Fit the MEM model for single subgroup using full Bayesian inference.

Usage

mem_single(
  responses,
  size,
  name,
  drug_index,
  p0 = 0.15,
  shape1 = 0.5,
  shape2 = 0.5,
  prior = rep(1, length(responses))/2,
  hpd_alpha = 0.05,
  alternative = "greater",
  call = NULL
)

Arguments

responses	the number of responses in each basket.
size	the size of each basket.
name	the name of each basket.
drug_index	the index of the basket to be studied.
p0	the null response rate for the poster probability calculation (default 0.15).
shape1	the first shape parameter(s) for the prior of each basket (default 0.5).
shape2	the second shape parameter(s) for the prior of each basket (default 0.5).
prior	the matrix giving the prior inclusion probability for each pair of baskets. The default is on on the main diagonal and 0.5 elsewhere.
hpd_alpha	the highest posterior density trial significance.
alternative	the alternative case definition (default greater)
call	the call of the function (default NULL).

Examples

# 6 baskets, each with enrollement size 5
trial_sizes <- rep(25, 6)

# The response rates for the baskets.
resp_rate <- 0.15

# The trials: a column of the number of responses and a column of the
# the size of each trial.
trials <- data.frame(
  responses = rbinom(trial_sizes, trial_sizes, resp_rate),
  size = trial_sizes,
  name = letters[1:6]
)

mem_single(trials$responses, trials$size, trials$name, drug_index = 2)

kaneplusplus/borrow documentation built on July 14, 2020, 1:50 a.m.