OPDOE (version 1.0-10)

triangular.test.prop: Triangular Test for Bernoulli Data

Description

Performs a sequential test, compares probabilities in two groups.

Usage

triangular.test.prop(x, y = NULL, p0 = NULL, p1 = NULL, p2 = NULL, alpha
= 0.05, beta = 0.1, delta = NULL, plot = TRUE)

Arguments

x

initial data for group x, at least 1 entry, values restricted to 0 and 1.

y

initial data for group y, at least 1 entry for a two sample test, otherwise omitted, values restricted to 0 and 1.

p0

specifies Null and alternative hypothesis, see Details below.

p1

specifies Null and alternative hypothesis, see Details below.

p2

specifies Null and alternative hypothesis, see Details below.

alpha

Risk of 1st kind

beta

Risk of 2nd kind

plot

logical, indicates whether a initial plot should be generated.

delta

The minimum difference to be detected, alternative way to specify p2=p1+delta, see above, use either this or p2.

Value

An object of class triangular.test, to be used for later update steps.

Details

One-sample:

This function performs a one- or two-sided sequential Test for \(p=\code{p1}\) versus

\(p>\code{p2}\), if p2 > p1 (one-sided)

\(p<\code{p2}\), if p2 < p1 (one-sided)

\(p<\code{p0}\) or \(p>\code{p2}\), if p2 > p1 and p0 < p1 (two-sided, possibly unsymmetric)

Two-sample:

This function performs a one- or two-sided sequential Test for equal proportions \(p_1=\code{p1}\) \(p_2=\code{p1}\) versus

\(p_2>\code{p2}\), if p2 > p1 (one-sided)

\(p_2<\code{p2}\), if p2 < p1 (one-sided)

\(p_2<\code{p0}\) or \(p_2>\code{p2}\), if p2 > p1 and p0 < p1 (two-sided, possibly unsymmetric)

References

Dieter Rasch, Juergen Pilz, L.R. Verdooren, Albrecht Gebhardt: Optimal Experimental Design with R, Chapman and Hall/CRC, 2011

See Also

triangular.test, triangular.test.norm, update.triangular.test

Examples

# NOT RUN {
data(heights)
attach(heights)
male180 <- as.integer(male>180) 
female164 <- as.integer(female>164)
sum(male180)/length(male180) 
tt <- triangular.test.prop(x=female164[1:3],
   y=male180[1:3], p1=0.4,p2=0.8,p0=0.1,
   alpha=0.05, beta=0.2)
tt <- update(tt,x=female164[4])
tt <- update(tt,y=male180[4])
tt <- update(tt,x=female164[5])
sum(female164)/length(female164)
# }