proportion (version 2.0.0)

pCOpBIEX: p-confidence and p-bias for Exact method given n and alpha level

Description

p-confidence and p-bias for Exact method given n and alpha level

Usage

pCOpBIEX(n, alp, e)

Arguments

n

- Number of trials

alp

- Alpha value (significance level required)

e

- Exact method indicator in [0, 1] 1: Clopper Pearson, 0.5: Mid P. The input can also be a range of values between 0 and 1.

Value

A dataframe with

x1

Number of successes (positive samples)

pconf

p-Confidence

pbias

p-Bias

e

- Exact method input

Details

Evaluation of Confidence interval for p based on inverting equal-tailed binomial tests with null hypothesis \(H0: p = p0\) using p-confidence and p-bias for the \(n + 1\) intervals

References

[1] 2005 Vos PW and Hudson S. Evaluation Criteria for Discrete Confidence Intervals: Beyond Coverage and Length. The American Statistician: 59; 137 - 142.

See Also

Other p-confidence and p-bias of base methods: PlotpCOpBIAS, PlotpCOpBIAll, PlotpCOpBIBA, PlotpCOpBIEX, PlotpCOpBILR, PlotpCOpBILT, PlotpCOpBISC, PlotpCOpBITW, PlotpCOpBIWD, pCOpBIAS, pCOpBIAll, pCOpBIBA, pCOpBILR, pCOpBILT, pCOpBISC, pCOpBITW, pCOpBIWD

Examples

n=5; alp=0.05;e=0.5
pCOpBIEX(n,alp,e)
n=5; alp=0.05;e=1 #Clopper-Pearson
pCOpBIEX(n,alp,e)
n=5; alp=0.05;e=c(0.1,0.5,0.95,1) #Range including Mid-p and Clopper-Pearson
pCOpBIEX(n,alp,e)