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Phylogenetic Pairwise Contrasts
A phylogenetic comparative method for finding associations between biological traits and molecular evolutionary rates. The method samples pairs from a phylogeny such that each pair has non-overlapping edge paths, and can therefore be treated as statistically independent observations. Linear regression is performed on the pair contrasts. This approach is similar to phylogenetically independent contrasts (PIC) but without reconstructing the traits at internal nodes, and is better suited for finding trait-rate associations than phylogenetic generalised least squares (PGLS). Refer to Douglas and Bromham (2026)
Statistical Methods for Psychologists
Implements confidence interval and sample size methods that are especially useful in psychological research but are also useful in educational, social science, business, and biological research. This package includes more than 100 confidence interval functions and more than 80 sample size functions for 1-group, 2-group, paired-samples, and multiple-group designs and for a variety of parameters including means, medians, proportions, slopes, standardized mean differences, standardized linear contrasts of means, and several measures of correlation and association. The sample size functions can be used to approximate the sample size needed to estimate a parameter or function of parameters with desired confidence interval precision or to perform a variety of hypothesis tests (directional two-sided, equivalence, superiority, noninferiority) with desired power. For details about these methods see: Statistical Methods for Psychologists, Volumes 1 – 4, < https://dgbonett.sites.ucsc.edu/>.
Econometric Tools for Performance and Risk Analysis
Collection of econometric functions for performance and risk analysis. In addition to standard risk and performance metrics, this package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.
Tool for Unbiased Literature Searching and Gene List Curation
Designed for genomic and proteomic data analysis, enabling unbiased PubMed searching, protein interaction network visualization, and comprehensive data summarization. This package aims to help users identify novel targets within their data sets based on protein network interactions and publication precedence of target's association with research context based on literature precedence. Methods in this package are described in detail in: Douglas et al. (2025)
Examples from Multilevel Modelling Software Review
Data and examples from a multilevel modelling software review as well as other well-known data sets from the multilevel modelling literature.
Benchmark the Performance of 'shiny' Applications
Compare performance between different versions of a 'shiny' application based on 'git' references.
Quick Multivariate Graphs
Functions used for graphing in multivariate contexts. These functions are designed to support produce reasonable graphs with minimal input of graphing parameters. The motivation for these functions was to support students learning multivariate concepts and R - there may be other functions and packages better-suited to practical data analysis. For details about the ellipse methods see Johnson and Wichern (2007, ISBN:9780131877153).
'R' 'Markdown' Format for 'shower' Presentations
'R' 'Markdown' format for 'shower' presentations, see < https://github.com/shower/shower>.
Approximate Marginal Inference for Regression-Scale Models
Implements likelihood inference based on higher order approximations for linear nonnormal regression models.
Probability of Sporulation Potential in MAGs
Implements an ensemble machine learning approach to predict the sporulation potential of metagenome-assembled genomes (MAGs) from uncultivated Firmicutes based on the presence/absence of sporulation-associated genes.