ciCASx: Continuity corrected ArcSine method of CI estimation

In proportion: Inference on Single Binomial Proportion and Bayesian Computations

Description

Continuity corrected ArcSine method of CI estimation

Usage

ciCASx(x, n, alp, c)

Arguments

x	- Number of successes
n	- Number of trials
alp	- Alpha value (significance level required)
c	- Continuity correction

Details

Wald-type interval for the arcsine transformation using the test statistic (abs(sin^(-1)phat-sin^(-1)p)-c)/SE where c > 0 is a constant for continuity correction and for all x = 0, 1, 2 ..n

Value

A dataframe with

x	Number of successes (positive samples)
LCAx	ArcSine Lower limit
UCAx	ArcSine Upper Limit
LABB	ArcSine Lower Abberation
UABB	ArcSine Upper Abberation
ZWI	Zero Width Interval

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.

Examples

x=5; n=5; alp=0.05;c=1/2*n
ciCASx(x,n,alp,c)

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