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lcc: Advanced Analysis of Longitudinal Data Using the Concordance
Correlation 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 |
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=lcc
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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