lcc

lcc estimates longitudinal concordance correlation, longitudinal Pearson correlation (LPC), and longitudinal accuracy (LA) to assess agreement between measurement methods or raters over time in longitudinal studies.

Key Features:

• Longitudinal Concordance Correlation (LCC): Estimates the LCC to evaluate agreement profiles of quantitative measurements across time.
• Longitudinal Pearson Correlation and Accuracy (LPC, LA): Estimates LPC and LA as complementary measures of association and accuracy over time.
• Polynomial Mixed-effects Regression: Employs polynomial mixed-effects regression models using fixed effects and variance components to model longitudinal trends.
• Variance-covariance Modeling: Handles variance-covariance matrices for random effects and residuals and supports different within-group error structures.
• Covariate Adjustment: Allows inclusion of covariates in the linear predictor to control systematic variations in responses.
• Study Design Flexibility: Accommodates balanced and unbalanced experimental and observational study designs.
• Bootstrap Confidence Intervals: Provides bootstrap-based confidence intervals for inference.
• Diagnostic Outputs: Produces diagnostic plots and statistical tests with numerical and graphical summaries.

Scientific Applications:

• Comparative Method Evaluation: Quantifies agreement and consistency between different measurement methods or raters over time.
• Longitudinal Agreement Analysis in Medicine, Pharmacology, and Agronomy: Assesses temporal agreement of quantitative measurements in longitudinal studies within these fields.

Methodology:

Estimation via polynomial mixed-effects regression models with fixed effects and variance components; modeling of variance-covariance matrices for random effects and residuals; inclusion of covariates in the linear predictor; inference using bootstrap confidence intervals; diagnostics via plots and statistical tests.