This is a collection of data and functions for common metrics in political science research. Data measuring ideology, and functions calculating geographical diffusion and ideological diffusion - geog.diffuse() and ideo.dist(), respectively. Functions derived from methods developed in: Soule and King (2006) <doi:10.1086/499908>, Berry et al. (1998) <doi:10.2307/2991759>, Cruz-Aceves and Mallinson (2019) <doi:10.1177/0160323X20902818>, and Grossback et al. (2004) <doi:10.1177/1532673X04263801>.

This package provides tools for downloading, reading and analyzing the National Survey of Demographic and Health - PNDS, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package survey'.

This package provides general linear model facilities (single y-variable, multiple x-variables with arbitrary mixture of continuous and categorical and arbitrary interactions) for cross-species data. The method is, however, based on the nowadays rather uncommon situation in which uncertainty about a phylogeny is well represented by adopting a single polytomous tree. The theory is in A. Grafen (1989, Proc. R. Soc. B 326, 119-157) and aims to cope with both recognised phylogeny (closely related species tend to be similar) and unrecognised phylogeny (a polytomy usually indicates ignorance about the true sequence of binary splits).

Programs to determine student grades and create examinations from Question banks. Programs will create numerous multiple choice exams, randomly shuffled, for different versions of same question list.

This package provides programmatic access to GitHub API with a focus on project management. Key functionality includes setting up issues and milestones from R objects or YAML configurations, querying outstanding or completed tasks, and generating progress updates in tables, charts, and RMarkdown reports. Useful for those using GitHub in personal, professional, or academic settings with an emphasis on streamlining the workflow of data analysis projects.

Palettes inspired by Paris 2024 Olympic and Paralympic Games for data visualizations. Length of color palettes is configurable.

Conduct permutation One-Way or Two-Way Analysis of Variance in R. Use different permutation types for two-way designs.

Computes the minimum sample size required for the external validation of an existing multivariable prediction model using the criteria proposed by Archer (2020) <doi:10.1002/sim.8766> and Riley (2021) <doi:10.1002/sim.9025>.

This package provides functions to load Research Patient Data Registry ('RPDR') text queries from Partners Healthcare institutions into R. The package also provides helper functions to manipulate data and execute common procedures such as finding the closest radiological exams considering a given timepoint, or creating a DICOM header database from the downloaded images. All functionalities are parallelized for fast and efficient analyses.

Interactions between different biological entities are crucial for the function of biological systems. In such networks, nodes represent biological elements, such as genes, proteins and microbes, and their interactions can be defined by edges, which can be either binary or weighted. The dysregulation of these networks can be associated with different clinical conditions such as diseases and response to treatments. However, such variations often occur locally and do not concern the whole network. To capture local variations of such networks, we propose multiplex network differential analysis (MNDA). MNDA allows to quantify the variations in the local neighborhood of each node (e.g. gene) between the two given clinical states, and to test for statistical significance of such variation. Yousefi et al. (2023) <doi:10.1101/2023.01.22.525058>.

This package provides functions and mined database from UniProt focusing on post-translational modifications to do single enrichment analysis (SEA) and protein set enrichment analysis (PSEA). Payman Nickchi, Uladzislau Vadadokhau, Mehdi Mirzaie, Marc Baumann, Amir Ata Saei, Mohieddin Jafari (2025) <doi:10.1002/pmic.202400238>.

This package provides functions to calculate and plot event and pointer years as well as resilience indices. Designed for dendroecological applications, but also suitable to analyze patterns in other ecological time series.

This package provides a wrapper for Paddle - The Merchant of Record for digital products API (Application Programming Interface) <https://developer.paddle.com/api-reference/overview>. Provides functions to manage and analyze products, customers, invoices and many more.

This package implements the methods proposed by Olley, G.S. and Pakes, A. (1996) <doi:10.2307/2171831>, Levinsohn, J. and Petrin, A. (2003) <doi:10.1111/1467-937X.00246>, Ackerberg, D.A. and Caves, K. and Frazer, G. (2015) <doi:10.3982/ECTA13408> and Wooldridge, J.M. (2009) <doi:10.1016/j.econlet.2009.04.026> for structural productivity estimation .

This package provides tools for retrieving and analyzing air quality data from PurpleAir sensors through their API. Functions enable downloading historical measurements, accessing sensor metadata, and managing API request limitations through chunked data retrieval. For more information about the PurpleAir API, see <https://api.purpleair.com/>.

This package provides a comprehensive framework for planning and executing analyses in R. It provides a structured approach to running the same function multiple times with different arguments, executing multiple functions on the same datasets, and creating systematic analyses across multiple strata or variables. The framework is particularly useful for applying the same analysis across multiple strata (e.g., locations, age groups), running statistical methods on multiple variables (e.g., exposures, outcomes), generating multiple tables or graphs for reports, and creating systematic surveillance analyses. Key features include efficient data management, structured analysis planning, flexible execution options, built-in debugging tools, and hash-based caching.

This package provides tools for Bayesian estimation of meta-analysis models that account for publications bias or p-hacking. For publication bias, this package implements a variant of the p-value based selection model of Hedges (1992) <doi:10.1214/ss/1177011364> with discrete selection probabilities. It also implements the mixture of truncated normals model for p-hacking described in Moss and De Bin (2019) <arXiv:1911.12445>.

Estimate commonly used population genomic statistics and generate publication quality figures. PopGenHelpR uses vcf, geno (012), and csv files to generate output.

This package provides functions for conventionally formatting descriptive stats, reshaping data frames and formatting R output as HTML.

This package provides a novel pseudo-value regression approach for the differential co-expression network analysis in expression data, which can incorporate additional clinical variables in the model. This is a direct regression modeling for the differential network analysis, and it is therefore computationally amenable for the most users. The full methodological details can be found in Ahn S et al (2023) <doi:10.1186/s12859-022-05123-w>.

Generates chronological and ordered p-plots for data vectors or vectors of p-values. The p-plot visualizes the evolution of the p-value of a significance test across the sampled data. It allows for assessing the consistency of the observed effects, for detecting the presence of potential moderator variables, and for estimating the influence of outlier values on the observed results. For non-significant findings, it can diagnose patterns indicative of underpowered study designs. The p-plot can thus either back the binary accept-vs-reject decision of common null-hypothesis significance tests, or it can qualify this decision and stimulate additional empirical work to arrive at more robust and replicable statistical inferences.

Data files and documentation for PEDiatric vALidation oF vAriableS in TBI (PEDALFAST). The data was used in "Functional Status Scale in Children With Traumatic Brain Injury: A Prospective Cohort Study" by Bennett, Dixon, et al (2016) <doi:10.1097/PCC.0000000000000934>.

This package provides functions to patch specials in .dvi files, or entries in .synctex files. Works with concordance=TRUE in Sweave, knitr or R Markdown to link sources to previews.

Enables computation of epidemiological statistics, including those where counts or mortality rates of the reference population are used. Currently supported: excess hazard models (Dickman, Sloggett, Hills, and Hakulinen (2012) <doi:10.1002/sim.1597>), rates, mean survival times, relative/net survival (in particular the Ederer II (Ederer and Heise (1959)) and Pohar Perme (Pohar Perme, Stare, and Esteve (2012) <doi:10.1111/j.1541-0420.2011.01640.x>) estimators), and standardized incidence and mortality ratios, all of which can be easily adjusted for by covariates such as age. Fast splitting and aggregation of Lexis objects (from package Epi') and other computations achieved using data.table'.