Description Usage Arguments Details Value References See Also Examples

View source: R/103.ConfidenceIntervals_BASE_n_x.R

Exact method of CI estimation

1 | ```
ciEXx(x, n, alp, e)
``` |

`x` |
- Number of sucess |

`n` |
- Number of trials |

`alp` |
- Alpha value (significance level required) |

`e` |
- Exact method indicator in [0, 1] 1: Clopper Pearson, 0.5: Mid P |

Confidence interval for `p`

(for the given `x`

and `n`

),
based on inverting equal-tailed binomial tests with null hypothesis *H0: p = p0 *
and calculated from the cumulative binomial distribution.
Exact two sided P-value is usually calculated as

*P= 2[e*Pr(X = x) + min({Pr(X < x), Pr(X > x)})]*

where probabilities are found at null value of `p`

and *0 <= e <= 1.*

A dataframe with

`x ` |
- Number of successes (positive samples) |

`LEXx ` |
- Exact Lower limit |

`UEXx ` |
- Exact Upper Limit |

[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`

, `ciAllx`

,
`ciBAx`

, `ciLRx`

,
`ciLTx`

, `ciSCx`

,
`ciTWx`

, `ciWDx`

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