errAWD: Calculates error, long term power and pass/fail criteria for...

In proportion: Inference on Single Binomial Proportion and Bayesian Computations

Description

Calculates error, long term power and pass/fail criteria for adjusted Wald method

Usage

errAWD(n, alp, h, phi, f)

Arguments

n	- Number of trials
alp	- Alpha value (significance level required)
h	- Adding factor
phi	- Null hypothesis value
f	- Failure criterion

Details

Evaluation of adjusted Wald-type interval using error due to the difference of achieved and nominal level of significance for the n + 1 intervals

Value

A dataframe with

delalp	Delta-alpha is the increase of the nominal error with respect to real error
theta	Long term power of the test
Fail_Pass	Fail/pass based on the input f criterion

References

[1] 2014 Martin Andres, A. and Alvarez Hernandez, M. Two-tailed asymptotic inferences for a proportion. Journal of Applied Statistics, 41, 7, 1516-1529

See Also

Other Error for adjusted methods: PloterrAAS, PloterrAAll, PloterrALR, PloterrALT, PloterrASC, PloterrATW, PloterrAWD, errAAS, errAAll, errALR, errALT, errASC, errATW

Examples

n=20; alp=0.05; h=2;phi=0.99; f=-2
errAWD(n,alp,h,phi,f)

proportion documentation built on May 1, 2019, 7:54 p.m.