phe_proportion: Calculate Proportions using phe_proportion

In publichealthengland/PHEindicatormethods: Common Public Health Statistics and their Confidence Intervals

Calculate Proportions using phe_proportion

Description

Calculates proportions with confidence limits using Wilson Score method (1,2).

Usage

phe_proportion(data, x, n, type = "full", confidence = 0.95, multiplier = 1)

Arguments

data	a data.frame containing the data to calculate proportions for, pre-grouped if proportions required for group aggregates; unquoted string; no default
x	field name from data containing the observed numbers of cases in the sample meeting the required condition (the numerator for the proportion); unquoted string; no default
n	field name from data containing the number of cases in the sample (the denominator for the proportion); unquoted string; no default
type	defines the data and metadata columns to be included in output; can be "value", "lower", "upper", "standard" (for all data) or "full" (for all data and metadata); quoted string; default = "full"
confidence	the required level of confidence expressed as a number between 0.9 and 1 or a number between 90 and 100. The vector c(0.95, 0.998) can also be passed to output both 95 percent and 99.8 percent CIs, or an NA value can be passed if no confidence intervals are required.; numeric; default 0.95
multiplier	the multiplier used to express the final values (eg 100 = percentage); numeric; default 1

Value

When type = "full", returns the original data.frame with the following appended: proportion, lower confidence limit, upper confidence limit, confidence level, statistic and method

Notes

Wilson Score method (2) is applied using the internal wilson_lower and wilson_upper functions.

The percentage argument was deprecated in v1_1_0, please use multiplier argument instead

References

(1) Wilson EB. Probable inference, the law of succession, and statistical inference. J Am Stat Assoc; 1927; 22. Pg 209 to 212.
(2) Newcombe RG, Altman DG. Proportions and their differences. In Altman DG et al. (eds). Statistics with confidence (2nd edn). London: BMJ Books; 2000. Pg 46 to 48.

See Also

Other PHEindicatormethods package functions: assign_funnel_significance(), calculate_ISRate(), calculate_ISRatio(), calculate_dsr(), calculate_funnel_limits(), calculate_funnel_points(), phe_dsr(), phe_life_expectancy(), phe_mean(), phe_quantile(), phe_rate(), phe_sii()

Examples

# ungrouped data frame
df <- data.frame(area = rep(c("Area1","Area2","Area3","Area4"), each=3),
                 numerator = c(NA,82,9,48, 6500,8200,10000,10000,8,7,750,900),
                 denominator = rep(c(100,10000,10000,10000), each=3))

phe_proportion(df, numerator, denominator)
phe_proportion(df, numerator, denominator, confidence=99.8)
phe_proportion(df, numerator, denominator, type="standard")
phe_proportion(df, numerator, denominator, confidence = c(0.95, 0.998))

# grouped data frame
library(dplyr)
dfg <- df |> group_by(area)
phe_proportion(dfg, numerator, denominator, multiplier=100)

publichealthengland/PHEindicatormethods documentation built on Dec. 15, 2024, 3:18 p.m.