rate: Calculate risk ratio and risk difference

In epijim/episheet: Rothman's Episheet

Calculate risk ratio and risk difference

Description

Calculate risk ratios and risk differences using a Poisson distribution for person-time data. Function works on individual level data or aggregated data p244 2nd Edition

Usage

rate(data, outcome, denominator, exposure, per_unit, ci_level = 95)

Arguments

data	A dataframe
outcome	Variable with the outcomes as a numeric variable
denominator	Variable giving the amount of time at risk
exposure	Variable giving whether exposed or not
per_unit	Multiplier for rate values, e.g. 1000 for n outcomes per 1000 denominator
ci_level	A numeric value giving the confidence interval

Examples

# Using individual level data

data(ebola)
library(dplyr)
ebola %>%
 mutate(male = ifelse(sex == "male", 1, 0)) %>%
  rate(outcome = died, denominator = days_at_risk, exposure = male,
  per_unit = 100)

# Using aggregated data
# Table 14-2
cancer_xray <- data.frame(cases = c(41, 15), pyar = c(28010, 19017),
radiation = c(1, 0))
cancer_xray
cancer_xray %>%
  rate(outcome = cases, denominator = pyar, exposure = radiation,
    per = 100000)

epijim/episheet documentation built on Jan. 5, 2024, 12:22 a.m.