Directly Standardise Rates by Age

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.

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