Mixed Models for Biological, Clustered and Longitudinal Data R package BioMixModel version 1.0.0 Fits and interprets mixed-effects models for clustered, longitudinal and heterogeneous biological data. Provides variance partitioning, intraclass correlation, penalized likelihood summaries, a heterogeneous-data information criterion, model comparison, diagnostics, and ensemble-style summaries for multilevel data. The package is designed as a complementary, interpretable workflow around established mixed-model methods. Methods for intraclass correlation and variance partitioning are informed by Nakagawa and Schielzeth (2010) <doi:10.1111/j.1469-185X.2010.00141.x> and Nakagawa et al. (2017) <doi:10.1098/rsif.2017.0213>. Mixed-effects modeling approaches are described by Zuur et al. (2009) <doi:10.1007/978-0-387-87458-6>. Software Depends: R (>= 4.1.0) Imports: stats, graphics Suggests: testthat (>= 3.0.0), glmmTMB, nlme, mgcv, survival, coxme, brms Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com> Comprehensive R Archive Network (CRAN) Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=BioMixModel/LICENSE) 2026-09-22 application/tgz https://CRAN.R-project.org/package=BioMixModel doi:10.32614/CRAN.package.BioMixModel en-US