Description Usage Arguments Details Value References See Also Examples

View source: R/descriptive_stats.R

`prec_prop`

returns the sample size or the precision for the provided
proportion.

1 2 3 4 5 6 7 8 |

`p` |
proportion. |

`n` |
number of observations. |

`conf.width` |
precision (the full width of the confidence interval). |

`conf.level` |
confidence level. |

`method` |
The method to use to calculate precision. Exactly one method may be provided. Methods can be abbreviated. |

`...` |
other arguments to uniroot (e.g. |

Exactly one of the parameters `n`

or `conf.width`

must be passed as NULL,
and that parameter is determined from the other.

The wilson, agresti-coull, exact, and wald method are implemented. The
wilson method is suggested for small `n`

(< 40), and the agresti-coull method
is suggested for larger `n`

(see reference). The wald method is not suggested,
but provided due to its widely distributed use.

`uniroot`

is used to solve `n`

for the agresti-coull,
wilson, and exact methods. Agresti-coull can be abbreviated by ac.

Object of class "presize", a list of arguments (including the
computed one) augmented with method and note elements. In the wilson and
agresti-coull formula, the p from which the confidence interval is
calculated is adjusted by a term (i.e. *p + term \pm ci*). This
adjusted p is returned in `padj`

.

Brown LD, Cai TT, DasGupta A (2001) *Interval Estimation for
a Binomial Proportion*, Statistical Science, 16:2, 101-117,
doi: 10.1214/ss/1009213286

`binom.test`

, `binom.confint`

in package binom, and `binconf`

in package
Hmisc

1 2 3 4 5 6 7 8 9 10 | ```
# CI width for 15\% with 50 participants
prec_prop(0.15, n = 50)
# number of participants for 15\% with a CI width of 0.2
prec_prop(0.15, conf.width = 0.2)
# confidence interval width for a range of scenarios between 10 and 90\% with
# 100 participants via the wilson method
prec_prop(p = 1:9 / 10, n = 100, method = "wilson")
# number of participants for a range of scenarios between 10 and 90\% with
# a CI of 0.192 via the wilson method
prec_prop(p = 1:9 / 10, conf.width = .192, method = "wilson")
``` |

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