assign_funnel_significance: Identifies whether each value in a dataset falls outside of...

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

Identifies whether each value in a dataset falls outside of 95 and/or 99.8 percent control limits based on the aggregated average value across the whole dataset as an indicator of statistically significant difference.

Description

This follows the funnel plot methodology published on the PHE Fingertips Technical Guidance page: https://fingertips.phe.org.uk/profile/guidance/supporting-information/PH-methods

Usage

assign_funnel_significance(
  data,
  numerator,
  denominator,
  rate,
  statistic = NULL,
  rate_type = NULL,
  multiplier = NULL
)

Arguments

data	a data.frame containing the data to assign significance for; unquoted string; no default
numerator	field name from data containing the observed numbers of cases in the sample meeting the required condition (the numerator or observed counts for the control limits); unquoted string; no default
denominator	field name from data containing the population(s) in the sample (the denominator or expected counts for the control limits); unquoted string; no default
rate	field name from data containing the rate data when creating funnels for a Crude or Directly Standardised Rate; unquoted string; no default
statistic	type of statistic to inform funnel calculations. Acceptable values are "proportion", "ratio" or "rate"; string; no default
rate_type	if statistic is "rate", specify either "dsr" or "crude"; string; no default
multiplier	the multiplier that the rate is normalised with (ie, per 100,000); only required when statistic = "rate"; numeric; no default

Value

returns the original data.frame with the significance level appended

Author(s)

Matthew Francis

See Also

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

Examples

library(dplyr)
df <- data.frame(
  Area = c("A", "B", "C", "D"),
  numerator = c(10232, 12321, 15123, 13213),
  denominator = c(15232, 16123, 17932, 18475)
)
df %>%
  assign_funnel_significance(numerator, denominator,
                             statistic = "proportion", multiplier = 100)

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