SQLite Interface for R

Embeds the SQLite database engine in R and provides an interface compliant with the DBI package. The source for the SQLite engine and for various extensions is included. System libraries will never be consulted because this package relies on static linking for the plugins it includes; this also ensures a consistent experience across all installations.

Flexible Time-to-Event Figures

Ease the creation of time-to-event (i.e. survival) endpoint figures. The modular functions create figures ready for publication. Each of the functions that add to or modify the figure are written as proper 'ggplot2' geoms or stat methods, allowing the functions from this package to be combined with any function or customization from 'ggplot2' and other 'ggplot2' extension packages.

Analysis Results Data

Construct CDISC (Clinical Data Interchange Standards Consortium) compliant Analysis Results Data objects. These objects are used and re-used to construct summary tables, visualizations, and written reports. The package also exports utilities for working with these objects and creating new Analysis Results Data objects.

D-Score for Child Development

The D-score summarizes a child's performance on developmental milestones into a single number. Its key feature is its generic nature. The method does not depend on a specific measurement instrument. The statistical method underlying the D-score is described in van Buuren et al. (2025) . This package implements model keys to convert milestone scores to D-scores; maps instrument-specific item names to a generic 9-position naming convention; computes D-scores and their precision from a child's milestone scores; and converts D-scores to Development-for-Age Z-scores (DAZ) using age-conditional reference standards.

Useful Tools for Structural Equation Modeling

Provides miscellaneous tools for structural equation modeling, many of which extend the 'lavaan' package. For example, latent interactions can be estimated using product indicators (Lin et al., 2010, ) and simple effects probed; analytical power analyses can be conducted (Jak et al., 2021, ); and scale reliability can be estimated based on estimated factor-model parameters.

Statistical Methods for Analytical Method Comparison and Validation

Provides statistical methods for analytical method comparison and validation studies. Implements Bland-Altman analysis for assessing agreement between measurement methods (Bland & Altman (1986) ), Passing-Bablok regression for non-parametric method comparison (Passing & Bablok (1983) ), and Deming regression accounting for measurement error in both variables (Linnet (1993) ). Also includes tools for setting quality goals based on biological variation (Fraser & Petersen (1993) ) and calculating Six Sigma metrics, precision experiments with variance component analysis, precision profiles for functional sensitivity estimation (Kroll & Emancipator (1993) < https://pubmed.ncbi.nlm.nih.gov/8448849/>). Commonly used in clinical laboratory method validation. Provides publication-ready plots and comprehensive statistical summaries.

Polygons with Holes for the Grammar of Graphics

Tools for working with polygons with holes in 'ggplot2', with a new 'geom' for drawing a 'polypath' applying the 'evenodd' or 'winding' rules.

Fits Poisson-Sum-of-Gammas GLMs, Tweedie GLMs, and Delta Log-Normal Models

Fits models to catch and effort data. Single-species models are 1) delta log-normal, 2) Tweedie, or 3) Poisson-gamma (G)LMs.

Estimating Systems of Simultaneous Equations

Econometric estimation of simultaneous systems of linear and nonlinear equations using Ordinary Least Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS), Weighted Two-Stage Least Squares (W2SLS), and Three-Stage Least Squares (3SLS) as suggested, e.g., by Zellner (1962) , Zellner and Theil (1962) , and Schmidt (1990) .

Large, Sparse Optimal Matching with Refined Covariate Balance

Tools for large, sparse optimal matching of treated units and control units in observational studies. Provisions are made for refined covariate balance constraints, which include fine and near-fine balance as special cases. Matches are optimal in the sense that they are computed as solutions to network optimization problems rather than greedy algorithms. See Pimentel, et al.(2015) and Pimentel (2016), Obs. Studies 2(1):4-23. The rrelaxiv package, which provides an alternative solver for the underlying network flow problems, carries an academic license and is not available on CRAN, but may be downloaded from Github at < https://github.com/josherrickson/rrelaxiv/>.