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

In RajeswaranV/proportion: Inference on Single Binomial Proportion and Bayesian Computations

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.

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

Value

A dataframe with

x1	Number of successes (positive samples)
pconf	p-Confidence
pbias	p-Bias
e	- Exact method input

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)

RajeswaranV/proportion documentation built on June 17, 2022, 9:11 a.m.