Learn R Programming

proportion (version 2.0.0)

ciALR: Adjusted Likelihood method of CI estimation

Description

Adjusted Likelihood method of CI estimation

Usage

ciALR(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)
LALR
Adjusted Likelihood Lower limit
UALR
Adjusted Likelihood Upper Limit
LABB
Adjusted Likelihood Lower Abberation
UABB
Adjusted Likelihood Upper Abberation
ZWI
Zero Width Interval

Details

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

Examples

Run this code
n=5; alp=0.05;h=2
ciALR(n,alp,h)

Run the code above in your browser using DataLab