- Example code in the documentation has been improved
- The package vignettes have been re-written
- The
standardize
function is now slightly easier to use: the standard population sizes provided bydata(standard)
can be passed to thestandardize
function without removing any unused age groups. Previously, it was necessary to subset thestandard
data before usingstandardize
.
Another short illustration of cancer data analysis with surveil
is provided here: https://connordonegan.github.io/surveil-paper/
This release was built using rstan
2.26.23, which incorporates Stan's new syntax for declaring arrays. Some models seems to run a little bit faster, but otherwise there are no changes that users should notice. This update should also address all warnings from tidyr regarding the use of deprecated tidyselect syntax.
The vignettes have been updated. The discussion of Markov chain Monte Carlo (MCMC) diagnostics, which was previously in the main package demo vignette, is now a stand-alone vignette with a bit of introductory discussion on MCMC analysis.
- The
stan_rw
model-fitting function now supports binomial models. - There is a new vignette on age-standardization and comparing risk across two age-stratified populations:
vignette("age-standardization")
. - The
group_diff
function, for calculating pairwise measures of inequality, can now be used to compare age-stratified populations. This includes a calculation of total annual (and cumulative) excess cases and attributable risk derived from all of the age-specific rates and population sizes. Seevignette("age-standardization")
. - A new
plot
method now accepts a list ofstand_surveil
objects. This will allow multiple standardized rates to be visualized on the same plot. - All plots have a new default, custom ggplot theme.
-
Previously, if multiple groups had been modeled, the cumulative percent change summary was printed incorrectly. Now, the print method will return a summary of the cumulative percent change for each group.
-
The plotting method for the group_diff object (pairwise inequality measures) has been adjusted so that the correct labels are used to identify the time periods on the x axis of the plots. Previously, if the
style = 'lines'
argument was used, the x axis used generic index values on the x axis instead of the labeled time periods provided by the user.
November 2021: surveil's first release.