JT.rank.SM: Calculates Jennison & Turnbull ranking of sample space

In CLAST: Exact Confidence Limits after a Sequential Trial

Calculates Jennison & Turnbull ranking of sample space

Description

Calculates the Jennison & Turnbull (1983) ranking of each possible outcome of the sample space generated from a sequential design.

Usage

JT.rank.SM(obj)

Arguments

obj	a list with elements S, M and design, containing all possible values of total successes S and stopping stage M based on the given design. Typically this is the output of function sample.space or sample.space.2 and will also have elements Y and decision.

Value

a list with element "lims" as well as all elements of argument obj. The extra element contains the JT rank of each possible the outcome.

Author(s)

Chris J. Lloyd

References

Jennison C, Turnbull BW. Confidence intervals for a binomial parameter following a multistage test with application to MIL-STD 105D and medical trials. Technometrics. 1983(25), 49-58. doi: 10.1080/00401706.1983.10487819

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.
JT.rank.SM(obj=all.samples)
# Component "lims" contains the rank of each sequential binary
# outcome. The same rank is assigned to outcomes with the same
# values of (S,M).

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