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clusteredMSM

Nonparametric Analysis of Clustered Multistate Processes

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().

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 clusteredMSM_0.1.0.tar.gz 150.8 KiB
0.1.0 rolling linux/noble R-4.5 clusteredMSM_0.1.0.tar.gz 150.9 KiB
0.1.0 rolling source/ R- clusteredMSM_0.1.0.tar.gz 66.4 KiB
0.1.0 latest linux/jammy R-4.5 clusteredMSM_0.1.0.tar.gz 150.8 KiB
0.1.0 latest linux/noble R-4.5 clusteredMSM_0.1.0.tar.gz 150.9 KiB
0.1.0 latest source/ R- clusteredMSM_0.1.0.tar.gz 66.4 KiB
0.1.0 2026-04-23 source/ R- clusteredMSM_0.1.0.tar.gz 0 B

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