prob.SM: Probability of sufficient statistics (S,M).

In CLAST: Exact Confidence Limits after a Sequential Trial

Probability of sufficient statistics (S,M).

Description

Calculates probability distribution of sufficient statistics (S,M) from sample space object.

Usage

prob.SM(data, p, m = NULL, s = NULL)

Arguments

data	list with components $Y, $S, $M, $design, $count. Thsi will typically be the output of sample.space or sample.space.2.
p	value of binary probability
m	number of stages at end of sequential trial
s	number of successes at end of sequential trial

Value

list with component $prob, $count, $subcount and matrix $data giving the $subcount different binary sequential outcomes that lead to $prob.

Author(s)

Chris J. Lloyd

References

Lloyd, C.J. (2020) Exact confidence limits after a group sequential single arm binary trial. Statistics in Medicine, Volume 38, 2389-2399. doi: 10.1002/sim.8909

Examples

n=c(5,6,5,9)
a=c(2,4,5,12)
b=c(5,9,11,13)
# There are 364 possible outcomes from this design which are
# listed in a natural systematic order by function sample.space.
all.samples=sample.space(n,a,b)
attributes(all.samples)
# Y contains the 364 possible sequential binary outcomes;
# M contains how many stages before the decision;
# S contains the total number of success that produces the decision;
# decision the final binary test result of H0 or H1.
prob.SM(all.samples,p=.5,m=3,s=11)

CLAST documentation built on April 8, 2022, 9:06 a.m.