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clusteredMSM  

Nonparametric Analysis of Clustered Multistate Processes
View on CRAN: Click here


Download and install clusteredMSM package within the R console
Install from CRAN:
install.packages("clusteredMSM")

Install from Github:
library("remotes")
install_github("cran/clusteredMSM")

Install by package version:
library("remotes")
install_version("clusteredMSM", "0.1.0")



Attach the package and use:
library("clusteredMSM")
Maintained by
Giorgos Bakoyannis
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-27
Latest Update: 2026-05-27
Description:
Nonparametric estimation of population-averaged transition probabilities, with cluster-bootstrap pointwise confidence intervals, simultaneous confidence bands, and two-sample Kolmogorov-Smirnov-type tests for clustered or independent multistate process data. Estimation follows Bakoyannis (2021) <doi:10.1111/biom.13327>; two-sample inference for the cluster-randomized and independent-samples designs follows Bakoyannis and Bandyopadhyay (2022) <doi:10.1007/s10463-021-00819-x>. Both methods use the working-independence Aalen-Johansen estimator. The package supports both progressive (acyclic) and non-monotone (e.g., illness-death with recovery) multistate processes, right censoring, left truncation, and informative cluster size. The user supplies data in interval format (one row per mutually-exclusive time interval per subject) and interacts with the package through a single formula-based function, patp().
How to cite:
Giorgos Bakoyannis (2026). clusteredMSM: Nonparametric Analysis of Clustered Multistate Processes. R package version 0.1.0, https://cran.r-project.org/web/packages/clusteredMSM. Accessed 12 Sep. 2026.
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