Description Usage Arguments Examples
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
1 |
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. |
ci_level |
A numeric value giving the confidence interval |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # 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)
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