Nonparametric Analysis of Clustered Multistate Processes R package clusteredMSM version 0.1.0 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(). Software Depends: R (>= 3.5.0) Imports: survival, stats, utils Suggests: mstate, testthat (>= 3.0.0), knitr, rmarkdown Giorgos Bakoyannis <gbakogia@iu.edu> Comprehensive R Archive Network (CRAN) Giorgos Bakoyannis [aut, cre] (ORCID: <https://orcid.org/0000-0002-2789-2497>) GPL-3 2026-05-27 application/tgz https://CRAN.R-project.org/package=clusteredMSM doi:10.32614/CRAN.package.clusteredMSM