popEpi is built for the needs of registry-based (large-scale) epidemiological analysis. This is in most part enabled by the efficient data.table package for handling and aggregating large data sets.
popEpi currently supplies some utility functions such as splitMulti
and get.yrs for preparing large data sets for epidemiological analysis.
Included are also a a few functions that can be used in
epidemiological analysis such as sir for estimating
standardized incidence/mortality ratios (SIRs/SMRs) and survtab for
estimating observed and relative/net survival as well as cumulative incidence
functions (CIFs). In particular, survtab implements the Ederer II
(Ederer and Heise (1959)) and
Pohar Perme estimators (Pohar Perme, Stare, and Esteve (2012)
tools:::Rd_expr_doi("10.1111/j.1541-0420.2011.01640.x")) and allows for easy
age-standardisation.
Since there are many benefits to using data.tables, popEpi returns
outputs by default in the data.table format where appropriate.
Since data.table
objects are usually modified by reference, this may have surprising side
effects for users uninitiated in using data.table. To ensure
that appropriate outputs are in the data.frame format, set
options("popEpi.datatable" = FALSE). However, data.table
usage is recommended due to better performance and testing coverage.
data.table is used
by most functions internally in both cases.
Maintainer: Joonas Miettinen joonas.miettinen@cancer.fi (ORCID)
Authors:
Matti Rantanen matti.rantanen@statfinn.com
Other contributors:
Karri Seppa karri.seppa@cancer.fi [contributor]
Useful links: