proportion (version 2.0.0)

ciATW: Adjusted WALD-T method of CI estimation

Description

Adjusted WALD-T method of CI estimation

Usage

ciATW(n, alp, h)

Arguments

n

- Number of trials

alp

- Alpha value (significance level required)

h

- adding factor

Value

A dataframe with

x

Number of successes (positive samples)

LATW

Adjusted WALD-T Lower limit

UATW

Adjusted WALD-T Upper Limit

LABB

Adjusted WALD-T Lower Abberation

UABB

Adjusted WALD-T Upper Abberation

ZWI

Zero Width Interval

Details

Given data x and n are modified as \(x + h\) and \(n + (2*h)\) respectively, where \(h > 0\) then approximate method based on a t_approximation of the standardized point estimator for all \(x = 0, 1, 2 ..n.\)

References

[1] 1998 Agresti A and Coull BA. Approximate is better than "Exact" for interval estimation of binomial proportions. The American Statistician: 52; 119 - 126.

[2] 1998 Newcombe RG. Two-sided confidence intervals for the single proportion: Comparison of seven methods. Statistics in Medicine: 17; 857 - 872.

[3] 2008 Pires, A.M., Amado, C. Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods. REVSTAT - Statistical Journal, 6, 165-197.

See Also

prop.test and binom.test for equivalent base Stats R functionality, binom.confint provides similar functionality for 11 methods, wald2ci which provides multiple functions for CI calculation , binom.blaker.limits which calculates Blaker CI which is not covered here and propCI which provides similar functionality.

Other Adjusted methods of CI estimation: PlotciAAS, PlotciAAllg, PlotciAAll, PlotciALR, PlotciALT, PlotciASC, PlotciATW, PlotciAWD, ciAAS, ciAAll, ciALR, ciALT, ciASC, ciAWD

Examples

n=5; alp=0.05;h=2
ciATW(n,alp,h)