Includes functions for mapping named lists to function arguments, random strings, pasting and combining rows together across columns, etc.

Render clinical submission tables, listings, and figures to RTF', LaTeX', Typst', HTML', PDF', and DOCX from pre-summarised data frames, with no external Java or SAS dependency. Features include decimal alignment via font metrics, multi-level column headers with passthrough leaves, predicate-targeted cell styling, footnotes, group-aware pagination, and figures that wrap a plot or image in the same page chrome as a table. Built for Clinical Data Interchange Standards Consortium (CDISC) Analysis Data Model (ADaM) workflows and regulatory submissions to agencies such as the Food and Drug Administration (FDA), European Medicines Agency (EMA), and Pharmaceuticals and Medical Devices Agency (PMDA).

This package provides a set of vectorised functions to calculate medical equations used in transplantation, focused mainly on transplantation of abdominal organs. These functions include donor and recipient risk indices as used by NHS Blood & Transplant, OPTN/UNOS and Eurotransplant, tools for quantifying HLA mismatches, functions for calculating estimated glomerular filtration rate (eGFR), a function to calculate the APRI (AST to platelet ratio) score used in initial screening of suitability to receive a transplant from a hepatitis C seropositive donor and some biochemical unit converter functions. All functions are designed to work with either US or international units. References for the equations are provided in the vignettes and function documentation.

Makes data wrangling with ID-related aspects more comfortable. Provides functions that make it easy to inspect various subject-generated ID codes (SGIC) for plausibility. Also helps with inspecting other common identifiers, ensuring that your data stays clean and reliable.

This package provides nonparametric permutation tests for testing all or any subset of random effects in linear and nonlinear mixed-effects models, without requiring normality or other distributional assumptions on random effects or errors. Three distribution-free variance-component estimators are implemented: Variance Least Squares ('VLS'), Method of Moments ('MM'), and Method of Moments with First-Order Approximation ('MMF'). A permutation procedure is used to obtain finite-sample p-values. Plotting functions support data exploration, model evaluation, and communication of results. Methods are described in Uwimpuhwe, Drikvandi, and Blozis (2026) <doi:10.1002/sim.70605>.

Formula-based user-interfaces to specific transformation models implemented in package mlt (<DOI:10.32614/CRAN.package.mlt>, <DOI:10.32614/CRAN.package.mlt.docreg>). Available models include Cox models, some parametric survival models (Weibull, etc.), models for ordered categorical variables, normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression (Lohse et al., 2017, <DOI:10.12688/f1000research.12934.1>). The underlying theory is described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>. An extension to transformation models for clustered data is provided (Barbanti and Hothorn, 2022, <DOI:10.1093/biostatistics/kxac048>) and a tutorial explains applications in survival analysis (Siegfried et al., 2025, <DOI:10.48550/arXiv.2402.06428>). Multivariate conditional transformation models (Klein et al, 2022, <DOI:10.1111/sjos.12501>) and shift-scale transformation models (Siegfried et al, 2023, <DOI:10.1080/00031305.2023.2203177>) can be fitted as well. The package contains an implementation of a doubly robust score test, described in Kook et al. (2024, <DOI:10.1080/01621459.2024.2395588>).

The main function of the package aims to update lmer()'/'glmer() models depending on their warnings, so trying to avoid convergence and singularity problems.

Computes dental caries indices (DMFT, DMFS, dmft, dmfs) from surface-level clinical examination data and produces odontogram heatmap visualizations of per-tooth-surface outcomes. Supports primary and permanent dentition with configurable teeth per quadrant (5 to 8), separate root and coronal caries tallying, long and wide input formats, stratified output, and FDI/Universal/quadrant tooth numbering conversion.

This package provides a unified workflow for choosing, running, and interpreting common statistical tests, from group comparisons and analysis of variance to regression, survival analysis, and diagnostic and agreement statistics. The package combines assumption checks, test selection, effect sizes, formatted results, plain-language interpretation, and a sample-size planning module covering continuous, binary, survival, ordinal, bioequivalence, and precision-based designs. Implemented methods follow standard references including Casella and Berger (2002, ISBN:9780534243128), Hollander et al. (2013, ISBN:9781118553299), Agresti (2013, ISBN:9780470463635), Cohen (1988, ISBN:9780805802832), Hosmer, Lemeshow and Sturdivant (2013, ISBN:9780470582473), and Julious (2010, ISBN:9781584887393).

Triad Log-Linear modelling of Imprinting Environmental interactions, and Maternal effects (TriLLIEM). This is an implementation of the log-linear model described in a series of papers, see for example Ainsworth et al. (2010) <doi:10.1002/gepi.20547>.

This package contains performance analysis metrics of track records including entropy-based correlation and dynamic beta based on a state/space algorithm. The normalized sample entropy method has been implemented which produces accurate entropy estimation even on smaller datasets. On a separate stream, trades from the five major assets classes and also functionality to use pricing curves, rating tables, Credit Support Annex and add-on tables. The implementation follows an object oriented logic whereby each trade inherits from more abstract classes while also the curves/tables are objects. Furthermore, odds calculators and P&L back-testing functionality has been implemented for the most widely used betting/trading strategies including martingale, DAlembert', Labouchere and Fibonacci. Back testing has also been included for the EuroMillions', the EuroJackpot', the UK Lotto, the Set For Life and the UK ThunderBall lotteries. Furthermore, some basic functionality about climate risk has been included.

This package provides functions for generating partially replicated (p-rep) test-control designs for early generation varietal trials conducted across multiple environments. The package implements three construction methods for obtaining p-rep test-control designs with one or more control treatments. The package extends the partially replicated design framework of Vinaykumar et al. (2026) <doi:10.1007/s12355-025-01684-1> to accommodate test-control comparisons in breeding trials. Functions are provided for generating randomized and non-randomized layouts and for displaying the design parameters and treatment allocations for each environment. The proposed designs are useful for large-scale varietal evaluation trials where a large number of test lines are assessed under limited experimental resources.

We focus on the diagnostic ability assessment of medical tests when the outcome of interest is the status (alive or dead) of the subjects at a certain time-point t. This binary status is determined by right-censored times to event and it is unknown for those subjects censored before t. Here we provide three methods (unknown status exclusion, imputation of censored times and using time-dependent ROC curves) to evaluate the diagnostic ability of binary and continuous tests in this context. Two references for the methods used here are Skaltsa et al. (2010) <doi:10.1002/bimj.200900294> and Heagerty et al. (2000) <doi:10.1111/j.0006-341x.2000.00337.x>.

Density, distribution function, quantile function and random generation for the Truncated Generalised Gamma Distribution (also in log10(x) and ln(x) space).

This package performs Thresholded Ordered Sparse Canonical Correlation Analysis (CCA). For more details see Senar, N. (2024) <doi:10.1093/bioadv/vbae021> and Senar, N. et al. (2025) <doi:10.48550/arXiv.2503.15140>.

C source code and R wrappers for the tth/ttm TeX-to-HTML/MathML translators.

This package performs multiple comparison analyses using Tukey's Honestly Significant Difference (HSD) test, with intuitive letter grouping of means for balanced and unbalanced designs. Accepts input from formula', aov', lm', aovlist', and lmerMod objects, including straightforward handling of interactions. For more details see Tukey (1949) <doi:10.2307/3001913>.

This package provides a tool to obtain tumor growth rates from clinical trial patient data. Output includes individual and summary data for tumor growth rate estimates as well as optional plots of the observed and predicted tumor quantity over time.

This package creates publication-ready tables documenting exponential-family random graph models (ERGMs), a class of statistical models for social networks (Robins et al., 2007, <doi:10.1016/j.socnet.2006.08.002>). Tables describe model terms through their definitions, mathematical representations, and graphical representations, and can be generated from ERGM formulas or from models fitted with the ergm package (Hunter et al., 2008, <doi:10.18637/jss.v024.i03>). Resulting tables can be integrated into quarto and rmarkdown documents.

Converting structured data from tables into XML format using predefined templates ensures consistency and flexibility, making it ideal for data exchange, reporting, and automated workflows.

Implementation of target diagrams using lattice and ggplot2 graphics. Target diagrams provide a graphical overview of the respective contributions of the unbiased RMSE and MBE to the total RMSE (Jolliff, J. et al., 2009. "Summary Diagrams for Coupled Hydrodynamic-Ecosystem Model Skill Assessment." Journal of Marine Systems 76: 64â 82.).

Writing an R value as JSON that a human can read, and reading it back unchanged. The jsonlite package offers either a readable but lossy pair of functions or a faithful but verbose one; this package emits ordinary JSON for ordinary values and annotates only what JSON cannot express, namely the distinction between integer and double, typed missing values, non-finite numbers, attributes, and objects from the S3, S4 and S7 systems.

This package provides reproducible tools for cleaning, parsing, classifying, standardising, validating and resolving scientific names in ecological and biodiversity datasets. Taxonomic matches can be assessed for match quality and taxonomic status, records requiring manual review can be identified, and resolution results can be summarised, reported and exported. Taxonomic name resolution can use the GBIF species matching service and the GBIF Backbone Taxonomy described by GBIF Secretariat (2023) <doi:10.15468/39omei>.

This package provides C++ header files for TinyDNG', a small header-only library for reading and writing DNG and TIFF files.