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vaccineff 1.0.0

CRAN release: 2024-11-29

{vaccineff 1.0.0} refactors the package’s internal structure for better maintainability.

Breaking Changes

  • estimate_vaccineff() replaces effectiveness().

    • It returns an object of class vaccineff.
    • The 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

New Features

{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 HRHR. A summary of the estimation is available via summary(), and a graphical representation of the methodology is generated by plot().

Breaking changes

The following functions are no longer accessible to users, but they are called within make_vaccineff_data():

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().

vaccineff 0.0.3

New Features

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.

vaccineff 0.0.2

New Features

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.

Breaking Changes

The following functions are no longer accessible to users. However, they are called within make_immunization():

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.