ciAllx: Specific CI estimation of 6 base methods (Wald, Wald-T,...
In proportion: Inference on Single Binomial Proportion and Bayesian Computations

Description Usage Arguments Details Value References See Also Examples

View source: R/103.ConfidenceIntervals_BASE_n_x.R

Specific CI estimation of 6 base methods (Wald, Wald-T, Likelihood, Score, Logit-Wald, ArcSine)

1	ciAllx(x, n, alp)

`x`	- Number of sucess
`n`	- Number of trials
`alp`	- Alpha value (significance level required)

The Confidence Interval of using 6 base methods (Wald, Wald-T, Likelihood, Score, Logit-Wald, ArcSine) for n given alp and x

A dataframe with

`name`	- Name of the method
`x`	- Number of successes (positive samples)
`LLT`	- Lower limit
`ULT`	- Upper Limit
`LABB`	- Lower Abberation
`UABB`	- Upper Abberation
`ZWI`	- Zero Width Interval

[1] 1993 Vollset SE. Confidence intervals for a binomial proportion. Statistics in Medicine: 12; 809 - 824.

[2] 1998 Agresti A and Coull BA. Approximate is better than "Exact" for interval estimation of binomial proportions. The American Statistician: 52; 119 - 126.

[3] 1998 Newcombe RG. Two-sided confidence intervals for the single proportion: Comparison of seven methods. Statistics in Medicine: 17; 857 - 872.

[4] 2001 Brown LD, Cai TT and DasGupta A. Interval estimation for a binomial proportion. Statistical Science: 16; 101 - 133.

[5] 2002 Pan W. Approximate confidence intervals for one proportion and difference of two proportions Computational Statistics and Data Analysis 40, 128, 143-157.

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

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

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 Base methods of CI estimation given x & n: PlotciAllxg, PlotciAllx, PlotciEXx, ciASx, ciBAx, ciEXx, ciLRx, ciLTx, ciSCx, ciTWx, ciWDx

1 2	x= 5; n=5; alp=0.05; ciAllx(x,n,alp)

      method x LowerLimit UpperLimit LowerAbb UpperAbb ZWI
1       Wald 5  1.0000000  1.0000000       NO       NO YES
2    ArcSine 5  0.8199137  0.8199137       NO       NO  NO
3 Likelihood 5  0.6810021  0.9999591       NO       NO  NO
4      Score 5  0.5655175  1.0000000       NO       NO  NO
5 Logit-Wald 5  0.4781762  1.0000000       NO       NO  NO
6     Wald-T 5  0.3359883  1.0000000       NO      YES  NO