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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 (2024) <doi:10.48550/arXiv.2411.12407>.
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Package details |
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| Author | Flora Le [aut, cre] (ORCID: <https://orcid.org/0000-0003-0089-8167>), Joshua F. Wiley [aut] (ORCID: <https://orcid.org/0000-0002-0271-6702>) |
| Maintainer | Flora Le <floralebui@gmail.com> |
| License | GPL (>= 3) |
| Version | 1.3.2 |
| URL | https://florale.github.io/multilevelcoda/ https://github.com/florale/multilevelcoda |
| Package repository | View on CRAN |
| Installation |
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