lcc: Advanced Analysis of Longitudinal Data Using the ConcordanceCorrelation Coefficient
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>.
| Version: | 3.2.2 |
| 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 |
| Published: | 2025-11-23 |
| DOI: | 10.32614/CRAN.package.lcc |
| Author: | Thiago de Paula Oliveira [aut, cre], Rafael de Andrade Moral [aut], Silvio Sandoval Zocchi [ctb], Clarice Garcia Borges Demetrio [ctb], John Hinde [aut] |
| Maintainer: | Thiago de Paula Oliveira <thiago.paula.oliveira at alumni.usp.br> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Citation: | lcc citation info |
| Materials: | README |
| CRAN checks: | lcc results |
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