ciALRx: AdjustedLikelyhood Ratio method of CI estimation

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

AdjustedLikelyhood Ratio method of CI estimation

Description

AdjustedLikelyhood Ratio method of CI estimation

Usage

ciALRx(x, n, alp, h)

Arguments

x	- Number of successes
n	- Number of trials
alp	- Alpha value (significance level required)
h	- Adding factor

Details

Likelihood ratio limits for the data x + h and n + (2*h) instead of the given x and n, where h is a positive integer (1, 2.) and for the given x and n.

Value

A dataframe with

x	Number of successes (positive samples)
LALRx	Likelyhood Ratio Lower limit
UALRx	Likelyhood Ratio Upper Limit
LABB	Likelyhood Ratio Lower Abberation
UABB	Likelyhood Ratio 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.

Other Adjusted methods of CI estimation given x & n: PlotciAAllx(), ciAASx(), ciAAllx(), ciALTx(), ciASCx(), ciATWx(), ciAWDx()

Examples

x=5; n=5; alp=0.05;h=2
ciALRx(x,n,alp,h)

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