PHEindicatormethods (version 1.1.5)

phe_rate: Calculate Rates using phe_rate

Description

Calculates rates with confidence limits using Byar's [1] or exact [2] CI method.

Usage

phe_rate(data, x, n, type = "full", confidence = 0.95,
  multiplier = 1e+05)

Arguments

data

the data.frame containing the data to calculate rates for, pre-grouped if proportions required for group aggregates; unquoted string; no default

x

field name from data containing the rate numerators (eg observed number of events); unquoted string; no default

n

field name from data containing the rate denominators (eg populations); 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 90 and 100; numeric; default 0.95

multiplier

the multiplier used to express the final values (eg 100,000 = rate per 100,000); numeric; default 100,000

Value

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

Notes

For numerators >= 10 Byar's method [1] is applied using the byars_lower and byars_upper functions. For small numerators Byar's method is less accurate and so an exact method [2] based on the Poisson distribution is used.

References

[1] Breslow NE, Day NE. Statistical methods in cancer research, volume II: The design and analysis of cohort studies. Lyon: International Agency for Research on Cancer, World Health Organisation; 1987. [2] Armitage P, Berry G. Statistical methods in medical research (4th edn). Oxford: Blackwell; 2002.

See Also

Other PHEindicatormethods package functions: phe_dsr, phe_isr, phe_life_expectancy, phe_mean, phe_proportion, phe_quantile, phe_sii, phe_smr

Examples

# NOT RUN {
# ungrouped data frame
df <- data.frame(area = rep(c("Area1","Area2","Area3","Area4"), each=3),
                 obs = c(NA,82,9,48, 6500,8200,10000,10000,8,7,750,900),
                 pop = rep(c(100,10000,10000,10000), each=3))

phe_rate(df, obs, pop)
phe_rate(df, obs, pop, type="standard")
phe_rate(df, obs, pop, confidence=99.8, multiplier=100)

# grouped data frame
library(dplyr)
dfg <- df %>% group_by(area)
phe_rate(dfg, obs, pop)

# }

Run the code above in your browser using DataCamp Workspace