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multilevelcoda

Estimate Bayesian Multilevel Models for Compositional Data

Implement Bayesian multilevel modelling for compositional data. Compute multilevel compositional data and perform log-ratio transforms at between and within-person levels, fit Bayesian multilevel models for compositional predictors and outcomes, and run post-hoc analyses such as isotemporal substitution models. References: Le, Stanford, Dumuid, and Wiley (2025) <doi:10.1037/met0000750>, Le, Dumuid, Stanford, and Wiley (2025) <doi:10.1080/00273171.2025.2565598>.

Versions across snapshots

VersionRepositoryFileSize
1.3.3 rolling linux/jammy R-4.5 multilevelcoda_1.3.3.tar.gz 4.1 MiB
1.3.3 rolling linux/noble R-4.5 multilevelcoda_1.3.3.tar.gz 4.1 MiB
1.3.3 rolling source/ R- multilevelcoda_1.3.3.tar.gz 4.3 MiB
1.3.3 latest linux/jammy R-4.5 multilevelcoda_1.3.3.tar.gz 4.1 MiB
1.3.3 latest linux/noble R-4.5 multilevelcoda_1.3.3.tar.gz 4.1 MiB
1.3.3 latest source/ R- multilevelcoda_1.3.3.tar.gz 4.3 MiB
1.3.3 2026-04-26 source/ R- multilevelcoda_1.3.3.tar.gz 4.3 MiB
1.3.3 2026-04-23 source/ R- multilevelcoda_1.3.3.tar.gz 4.3 MiB
1.3.3 2026-04-09 windows/windows R-4.5 multilevelcoda_1.3.3.zip 4.1 MiB
1.3.1 2025-04-20 source/ R- multilevelcoda_1.3.1.tar.gz 4.3 MiB

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