{vaccineff 1.0.0} refactors the package's internal structure for better
maintainability.
estimate_vaccineff() replaces effectiveness().
vaccineff.at parameter must always be provided for accurate results.plot.vaccineff_data() replaces plot_coverage().
cohortdata has been simplified and reduced to improve examples and
reduce computation time.
{vaccineff 0.0.4} simplifies data handling by using
linelist objects. Tags are
assigned to the outcome, censoring, and vaccine dates using the function
make_vaccineff_data(), reducing redundancy in function input parameters.
The new pipeline includes the following three functions and complementary
methods: summary and plot.
make_vaccineff_data(): This function returns an S3 object of the class
vaccineff_data() with the study's relevant information. It also allows
the creation of a matched cohort to control for confounding variables by
setting match = TRUE and passing the appropriate exact and nearest
arguments. The method summary() can be used to check cohort
characteristics, matching balance, and the sizes of matched, excluded,
and removed populations.
plot_coverage(): This function returns a plot of the vaccine coverage
or cumulative coverage. If the population is matched, the plot includes
the resulting count of doses after matching.
effectiveness(): This function provides methods for estimating VE using
the $HR$. A summary of the estimation is available via summary(), and
a graphical representation of the methodology is generated by plot().
The following functions are no longer accessible to users, but they are called
within make_vaccineff_data():
make_immunization()match_cohort()The plot() method returns log-log and survival type plots when receiving
an object of type effectiveness. This deprecates the functions plot_survival()
and plot_loglog().
This version introduces an iterative matching routine within match_cohort().
After adjusting the exposure times of the pairs, new pairs are created between
the removed ones and the unmatched population. The new matches with inconsistent
exposure times are removed again, and the procedure is repeated until no new
pairs can be made. The usage of all the functions remains unchanged by this update.
The number of functions and steps for computing vaccine effectiveness has
been drastically reduced in {vaccineff 0.0.2}. The new pipeline for
estimation now consists of three main functions:
make_immunization(): Prepares information on immunization dates
and vaccine status. It can handle multiple columns for vaccine dates and
custom vaccine statuses. In such cases, it returns the name of the column
selected as immunizing and the custom name, if provided.
match_cohort(): This function has been improved and generalized
to reduce observation bias in cohorts. The default matching strategy is
static, based on nearest and exact characteristics using Mahalanobis
distance. The exposure times of the pairs are adjusted after matching. In
future releases, rolling calendar matching will be introduced as a more
accurate method to account for exposure times. The function returns an S3
object of class match, from which a summary and balance of the cohorts
can be printed using the summary() method. The matched cohort can be
extracted using the get_dataset() method. The matched cohort contains
all the necessary information to estimate vaccine effectiveness.
effectiveness(): Receives a (matched) cohort and estimates vaccine
effectiveness using the Hazard Ratio (HR). An S3 object of class
effectiveness is returned, compatible with the plot() and summary()
methods. Future releases will provide relative risk (RR) as an alternative
for cases where the proportional hazards assumption is not satisfied.
The following functions are no longer accessible to users. However, they
are called within make_immunization():
get_immunization_date()get_immunization_dose()get_immunization_vaccine()set_status()Similarly, the effectiveness() function deprecates the use of
coh_eff_noconf(), and the plot() method now returns a log-log plot,
replacing the plot_loglog() function.