Description Usage Arguments Details Value References See Also Examples

View source: R/103.ConfidenceIntervals_BASE_n_x.R

Wald method of CI estimation

1 | ```
ciWDx(x, n, alp)
``` |

`x` |
- Number of successes |

`n` |
- Number of trials |

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

Wald-type interval that results from inverting
large-sample test and evaluates standard errors at maximum likelihood estimates
for the given `x`

and `n`

A dataframe with

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

`LWDx ` |
Wald Lower limit |

`UWDx ` |
Wald Upper Limit |

`LABB ` |
Wald Lower Abberation |

`UABB ` |
Wald 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`

, `ciAllx`

,
`ciBAx`

, `ciEXx`

,
`ciLRx`

, `ciLTx`

,
`ciSCx`

, `ciTWx`

1 2 | ```
x=5; n=5; alp=0.05;
ciWDx(x,n,alp)
``` |

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