View source: R/101.Confidence_base_n.R
| ciAS | R Documentation |
ArcSine method of CI estimation
ciAS(n, alp)
n |
- Number of trials |
alp |
- Alpha value (significance level required) |
Wald-type interval for all x = 0, 1, 2 ..n using the arcsine transformation of the parameter p; that is based on the normal approximation for sin-1(p).
Calculates the Confidence Interval of n given alp along with lower and upper abberation.
A dataframe with
x |
- Number of successes (positive samples) |
LAS |
- ArcSine Lower limit |
UAS |
- ArcSine Upper Limit |
LABB |
- ArcSine Lower Abberation |
UABB |
- ArcSine 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 Basic methods of CI estimation:
PlotciAS(),
PlotciAllg(),
PlotciAll(),
PlotciBA(),
PlotciEX(),
PlotciLR(),
PlotciLT(),
PlotciSC(),
PlotciTW(),
PlotciWD(),
ciAll(),
ciBA(),
ciEX(),
ciLR(),
ciLT(),
ciSC(),
ciTW(),
ciWD()
n=5; alp=0.05 ciAS(n,alp)
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