{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 classvaccineff_data
with the study's relevant information. It also allows the creation of a matched cohort to control for confounding variables by settingmatch = TRUE
and passing the appropriateexact
andnearest
arguments. The methodsummary()
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 viasummary()
, and a graphical representation of the methodology is generated byplot()
.
Breaking changes
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()
.
Get started with {vaccineff 0.0.4}
# Create `vaccineff_data`
vaccineff_data <- make_vaccineff_data(
data_set = cohortdata,
outcome_date_col = "death_date",
censoring_date_col = "death_other_causes",
vacc_date_col = "vaccine_date_2",
vaccinated_status = "v",
unvaccinated_status = "u",
immunization_delay = 15,
end_cohort = as.Date("2044-12-31"),
match = TRUE,
exact = c("age", "sex"),
nearest = NULL
)
# Print summary of vaccineff data object
summary(vaccineff_data)
# Plot the vaccine coverage of the total population
plot_coverage(vaccineff_data)
# Estimate the Vaccine Effectiveness at 90 days
ve90 <- effectiveness(vaccineff_data, at = 90)
# Print summary of VE
summary(ve90)
# Loglog plot to check proportional hazards
plot(ve90, type = "loglog")