A dataframe-friendly implementation of ComBat Harmonization which uses an empirical Bayesian framework to remove batch effects.
    Johnson WE & Li C (2007)  <doi:10.1093/biostatistics/kxj037> "Adjusting batch effects in microarray expression data using empirical Bayes methods."
    Fortin J-P, Cullen N, Sheline YI, Taylor WD, Aselcioglu I, Cook PA, Adams P, Cooper C, Fava M, McGrath PJ, McInnes M, Phillips ML, Trivedi MH, Weissman MM, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.11.024> "Harmonization of cortical thickness measurements across scanners and sites."
    Fortin J-P, Parker D, Tun<e7> B, Watanabe T, Elliott MA, Ruparel K, Roalf DR, Satterthwaite TD, Gur RC, Gur RE, Schultz RT, Verma R, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.08.047> "Harmonization of multi-site diffusion tensor imaging data."

A complete rewrite and reimagining of 'bakR' (see 'Vock et al.' (2025) <doi:10.1371/journal.pcbi.1013179>).
  Designed to support a wide array of analyses of nucleotide recoding RNA-seq (NR-seq) datasets of any
	type, including TimeLapse-seq/SLAM-seq/TUC-seq, Start-TimeLapse-seq (STL-seq),
	TT-TimeLapse-seq (TT-TL-seq), and subcellular NR-seq. 'EZbakR' extends
	standard NR-seq standard NR-seq mutational modeling to support multi-label analyses
	(e.g., 4sU and 6sG dual labeling), and implements an improved hierarchical model to better
	account for transcript-to-transcript variance in metabolic label incorporation.
	'EZbakR' also generalized dynamical systems modeling of NR-seq data to support analyses
	of premature mRNA processing and flow between subcellular compartments. Finally,
	'EZbakR' implements flexible and well-powered comparative analyses of all
	estimated parameters via design matrix-specified generalized linear modeling.

A tool to operate a batch of univariate or multivariate Cox
    models and return tidy result.

Calculate cutoff values for model fit measures used in structural equation modeling (SEM) by simulating and testing data sets (cf. Hu & Bentler, 1999 <doi:10.1080/10705519909540118>) with the same parameters (population model, number of observations, etc.) as the model under consideration.