Advanced Analysis of Longitudinal Data Using the Concordance Correlation Coefficient R package lcc version 3.2.2 Methods for assessing agreement between repeated measurements obtained by two or more methods using the longitudinal concordance correlation coefficient (LCC). Polynomial mixed-effects models (via 'nlme') describe how concordance, Pearson correlation and accuracy evolve over time. Functions are provided for model fitting, diagnostic plots, extraction of summaries, and non-parametric bootstrap confidence intervals (including parallel computation), following Oliveira et al. (2018) <doi:10.1007/s13253-018-0321-1>. Software Depends: R (>= 3.2.3), nlme (>= 3.1-124), ggplot2 (>= 2.2.1) Imports: hnp, parallel, doSNOW, doRNG, foreach Suggests: roxygen2 (>= 3.0.0), covr, testthat, MASS Thiago de Paula Oliveira <thiago.paula.oliveira@alumni.usp.br> Comprehensive R Archive Network (CRAN) Thiago de Paula Oliveira [aut, cre] (ORCID: <https://orcid.org/0000-0002-4555-2584>), Rafael de Andrade Moral [aut] (ORCID: <https://orcid.org/0000-0002-0875-3563>), Silvio Sandoval Zocchi [ctb] (ORCID: <https://orcid.org/0000-0003-2535-908X>), Clarice Garcia Borges Demetrio [ctb] (ORCID: <https://orcid.org/0000-0002-3609-178X>), John Hinde [aut] (ORCID: <https://orcid.org/0000-0001-6507-5204>) GPL (>= 2) 2025-11-23 application/tgz https://CRAN.R-project.org/package=lcc doi:10.32614/CRAN.package.lcc