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lcc

lcc is a package under development based on estimation procedures for longitudinal concordance correlation (lcc), longitudinal Pearson correlation (lpc), and longitudinal accuracy (la) through fixed effects and variance components of polynomial mixed-effect regression model. The main features of the package are its ability to perform inference about the extent of agreement and use a numerical and graphical to summary the fitted values, sampled values, and confidence intervals. Morever, our approach accommodate balanced or unbalanced experimental design, allows to model heteroscedasticity among within-group errors using or not the time as covariate, and also allows for inclusion of covariates in the linear predictor to control systematic variations in the response variable. It was developed by Thiago de Paula Oliveira [cre, aut], Rafael de Andrade Moral [aut], John Hinde [aut], Silvio Sandoval Zocchi [ctb], Clarice Garcia Borges Demétrio [ctb].

It has been available on CRAN since 2018 (https://CRAN.R-project.org/package=lcc). Its last version was updated on 2021-02-26. CRAN has lcc's stable version, which is recommended for most users.

This github page has its version under development. New functions will be added as experimental work and, once it is done and running correctly, we will synchronize the repositories and add it to the CRAN.

We worked hard to release a new stable version allowing users to analyze data sets, where the objective is studied the extent of the agreement profile among methods considering time as covariable.

lcc comprises a set of functions that allows users build and summaries the fitted model, estimates and bootstrap confidence intervals for lcc, lpc and la statistics, and build graphical summaries for them. Some functions are used internally by the package, and should not be used directly.

Installation

Installed from CRAN:

install.packages("lcc")

Installed the development version from Github:

install.packages("devtools")
devtools::install_github("Prof-ThiagoOliveira/lcc")

If you use Windows, first install Rtools. If you are facing problems with Rtools installation, try to do it by selecting Run as Admnistrator option with right mouse button. On a Mac, you will need Xcode (available on the App Store).

lcc can also be installed by downloading the appropriate files directly at the CRAN web site and following the instructions given in the section 6.3 Installing Packages of the R Installation and Administration manual.

Longitudinal Concordance Correlation App

We hope you learn more about the LCC using the LCC App. We develop this application to facilitate understanding of how each parameter can affects the LCC estimate over time. Have fun!

Tutorials

You can read lcc tutorials going to our work published at PeerJ (https://doi.org/10.7717/peerj.9850), or by clicking in the link below:

LCC paper.

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Version

Install

install.packages('lcc')

Monthly Downloads

294

Version

3.2.2

License

GPL (>= 2)

Maintainer

Thiago de Paula Oliveira

Last Published

November 23rd, 2025

Functions in lcc (3.2.2)

lccInternal

Internal Function to Prepare lcc Objects
plotBuilder_lpc

Internal Function to Produce a Longitudinal Pearson Correlation Plot
plot_la

Internal Function to Prepare the plotBuilder_la Function
plot_lpc

Prepare Plot for LPC Function
formatColumn

Format Columns for Print
hue

Hue color data
fittedBuilder

Internal Function to Build Fitted Values for lcc Objects
init

Internal Function to Prepare lccModel Function
simulated_hue

Hue color simulated data
lccBuilder

Internal Function to Estimate the Longitudinal Concordance Correlation
lccPlot

Plot Fitted Curves from an lcc Object
getVarCov.lcc

Extract Variance Components from a Fitted lcc Model
residuals.lcc

Extract Residuals from a Fitted lcc Model
lccSummary

Internal Function to Summarize Fitted and Sampled Values for lcc Objects
getDelta

Internal Function to Extract Variance Components Estimates.
simulated_hue_block

Hue color simulated data in a randomized block design
vcov.lcc

Extract Variance-Covariance Matrix of the Fixed Effects for an lcc Object
plotControl

Control Settings for lcc Plots
rename.vars

Internal Function to Prepare lccModel Function
lcc_intervals

Internal Functions to Compute the Non-Parametric Confidence Intervals for LCC.
plotBuilder_la

Internal Function to Produces a Longitudinal Accuracy Plot.
lccModel

Internal function to fit a linear mixed-effects model
summary.lcc

Summarize an lcc Object
logLik.lcc

Extract Log-Likelihood of an lcc Object
plotBuilder_lcc

Generate a Longitudinal Concordance Correlation Plot
print.summary.lcc

Print Summary of an lcc Object
plot.lcc

Diagnostic Plots for an lcc Object
lpcBuilder

Internal Function to Estimate the Longitudinal Pearson Correlation
print.anova.lcc

Print the Anova of an lcc Object
print.lcc

Print Method for lcc Objects
ranef.lcc

Extract Random Effects from an lcc Model
time_lcc

Regular Sequence Generator for Time Variable
Pearson

Estimate Sampled Pearson Correlation
anova.lcc

Compare Likelihoods of Fitted Models from an lcc Object
coef.lcc

Extract Model Coefficients
AIC.lcc

Akaike and Bayesian Information Criteria for an lcc Object
CCC

Internal Function to Compute the Sampled Concordance Correlation Values.
.compute_LPC

Internal helper to compute LPC list (does not depend on diffbeta)
.lcc_default_theme

Internal base theme used by all ggplot-based summaries
dataBuilder

Internal Function to Prepare the Dataset for lcc Objects
ciBuilder

Internal Function to Prepare the ciCompute Function.
bootstrapSamples

Internal functions to estimate fixed effects and variance components.
ciCompute

Internal Function to Compute the Non-Parametric Bootstrap Interval.
.precompute_longitudinal

Internal helper to precompute longitudinal quantities
CCC_lin

Internal Function to Estimate the Sampled Concordance Correlation Coefficient.
.compute_LA

Internal helper to compute LA list for one diffbeta
lcc

Longitudinal concordance correlation (LCC) from polynomial mixed effects regression models using fixed effects and variance components
fitted.lcc

Extract Fitted Values from an lcc Object
.compute_LCC

Internal helper to compute LCC list for one diffbeta
is.lcc

Reports whether x is a lcc object
laBuilder

Internal Function to Estimate the Longitudinal Accuracy (Bias Corrector)