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mccount Hexagonal logo for the R package 'mccount' featuring a cartoon vampire resembling the Count from Sesame Street, styled as a hip-hop MC with a snapback hat labeled 'mccount', gold chain with a Sigma pendant, monocle, and microphone, set against a red brick background.

Lifecycle: experimental CRAN status CRAN RStudio mirror downloads R-CMD-check Codecov test coverage

Overview

mccount provides tools to estimate the mean cumulative count (MCC) of recurrent events in the presence of competing risks. Unlike traditional cumulative incidence methods that only consider the first occurrence of an event, MCC accounts for multiple occurrences of the same event type per individual, providing a more informative measure of the total burden of recurrent events in a population.

Available MCC methods in this package include the Dong-Yasui or the sum of cumulative incidences estimators, based on the work of Dong, et al.1 Users can also estimate the MCC using the weighted Dong-Yasui estimator.2

Installation

You can install mccount from CRAN using the following code:

install.packages("mccount")

Development version

You can install the development version of mccount like so:

# install.packages("pak")
pak::pkg_install("KennethATaylor/mccount")

Why Mean Cumulative Count?

In the context of clinical and epidemiological studies, subjects may experience multiple recurrent events over a given follow-up period. Traditional methods like Kaplan-Meier or cumulative incidence only account for the first occurrence of an event and ignore subsequent recurrent events, which can lead to underestimation of the true disease burden.

The MCC:

Citation

If you use mccount in your research, please cite the package in addition to the relevant original methodology paper(s).

citation("mccount")

  1. Dong H, Robison LL, Leisenring WM, Martin LJ, Armstrong GT, Yasui Y. Estimating the burden of recurrent events in the presence of competing risks: the method of mean cumulative count. Am J Epidemiol. 2015 Apr 1;181(7):532-40. doi: 10.1093/aje/kwu289↩︎

  2. Gaber CE, Edwards JK, Lund JL, Peery AF, Richardson DB, Kinlaw AC. Inverse Probability Weighting to Estimate Exposure Effects on the Burden of Recurrent Outcomes in the Presence of Competing Events. Am J Epidemiol. 2023;192(5):830-839. doi: 10.1093/aje/kwad031↩︎

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.