exact.lower.limits.SM {CLAST} R Documentation

## Calculates all exact lower limits.

### Description

Calculates Buehler lower limit for all possible data sets based on a provided ranking function.

### Usage

exact.lower.limits.SM(obj, lims = NULL, alpha = 0.05, set = FALSE)


### Arguments

 obj list with components $count,$S, $N, typically the output of LR.stats.SM, CP.stats.SM, JT.rank.SM or ML.rank.SM. In this case, it will also have element$lims. lims a vector of same length as obj$count, most often an approximate lower limits. If this is missing, then it should be an element of obj$lims. alpha exact coverage error set If true, exact limits of 1 are replaced by the largest limit less than 1. This will never be chosen by the user and is there for certain numerical investigations.

A numeric vector of same length as obj$lims, giving the exact lower limit for each possible outcome as listed in components obj$M and obj$S. ### Author(s) Chris J. Lloyd ### References Lloyd, C.J. (2020) Exact confidence limits after a group sequential single arm binary trial. Statistics in Medicine, Volume 38, 2389-2399. ### Examples # Example 1 in table 1 of Lloyd (2020) n=c(5,6,5,9) a=c(2,4,5,12) b=c(5,9,11,13) # There are 364 possible outcomes from this design which are # listed in a natural systematic order by function sample.space. all.samples=sample.space.SM(n,a,b) attributes(all.samples) # Y contains the 364 possible sequential binary outcomes; # M contains how many stages before the decision; # S contains the total number of success that produces the decision; # decision the final binary test result of H0 or H1. all.CP=CP.stats.SM(all.samples,type="lower") all.CP$lims # These limits are based on fixed sample size so are not edxact.
all.exact=exact.lower.limits.SM(all.CP)
plot(all.CP\$lims,all.exact)


[Package CLAST version 1.0.1 Index]