Description
Directly Standardise Rates by Age.
Description
Provides functions for age standardisation of epidemiological measures such as incidence and prevalence rates. It allows users to apply standard population structures to observed age-specific estimates in order to obtain comparable summary measures across populations or time periods. Functions support calculation of standardised rates, outcome counts, and corresponding confidence intervals. The tools are designed to facilitate reproducible and transparent adjustment for differences in age distributions in epidemiological and public health research.
README.md
EpiStandard 
The goal of EpiStandard is to provide functions to allow for age standardisation of results produced from epidemiological studies.
Installation
The package can be installed from CRAN:
install.packages("EpiStandard")
You can install the development version of EpiStandard from GitHub with:
# install.packages("devtools")
devtools::install_github("oxford-pharmacoepi/EpiStandard")
Main functionalities
library(EpiStandard)
The main functionality of the package is to calculate directly standardised rates.
Example
df_study <- data.frame(state=rep(c('Miami',"Alaska"), c(5,5)),
age=rep(c('0-14','15-24','25-44','45-64','65-150'),2),
deaths=c(136,57,208,1016,3605,59,18,37,90,81),
fu=c(114350,80259,133440,142670,92168,37164,20036,32693,14947,2077))
#US standard population
df_ref <- data.frame(age=c('0-14','15-24','25-44','45-64','65-150'),
pop=c(23961000,15420000,21353000,19601000,10685000))
#Directly standardised Rates (per 1000) - 95% CI's using the gamma method
my_results <- directlyStandardiseRates(data = df_study,
event = "deaths",
denominator = "fu",
strata = "state",
age = "age",
refdata = df_ref)
my_results |> dplyr::glimpse()
## Rows: 2
## Columns: 9
## $ state <chr> "Miami", "Alaska"
## $ deaths <dbl> 5022, 285
## $ fu <dbl> 562887, 106917
## $ crude_rate <dbl> 892.1862, 266.5619
## $ crude_rate_95CI_lower <dbl> 867.5107, 235.6145
## $ crude_rate_95CI_upper <dbl> 916.8616, 297.5093
## $ standardised_rate <dbl> 692.4240, 671.0406
## $ standardised_rate_95CI_lower <dbl> 673.0405, 566.6666
## $ standardised_rate_95CI_upper <dbl> 711.8074, 775.4146