Frequentist statistical inference for cluster randomised trials with multiple outcomes that controls the family-wise error rate and provides nominal coverage of confidence sets. A full description of the methods can be found in Watson et al. (2023) <doi:10.1002/sim.9831>.

This package contains functions that check for formatting of the Subject Phenotype data set and data dictionary as specified by the National Center for Biotechnology Information (NCBI) Database of Genotypes and Phenotypes (dbGaP) <https://www.ncbi.nlm.nih.gov/gap/docs/submissionguide/>.

This package provides tools to compute directly age-standardised rates using the 2013 European Standard Population. Includes variance estimation and 95% confidence intervals for population health applications. Functions are flexible to handle any grouping variable and age bands, allowing reproducible and automated analyses.

This package provides functions to justify alpha levels for statistical hypothesis tests by avoiding Lindley's paradox, or by minimizing or balancing error rates. For more information about the package please read the following: Maier & Lakens (2021) <doi:10.31234/osf.io/ts4r6>).

Efficient way to design and conduct psychological experiments for testing the performance of large language models. It simplifies the process of setting up experiments and data collection via language modelsâ API, facilitating a smooth workflow for researchers in the field of machine behaviour.

Providing functions to diagnose and make inferences from various linear models, such as those obtained from aov', lm', glm', gls', lme', lmer', glmmTMB and semireg'. Inferences include predicted means and standard errors, contrasts, multiple comparisons, permutation tests, adjusted R-square and graphs.

Free UK geocoding using data from Office for National Statistics. It is using several functions to get information about post codes, outward codes, reverse geocoding, nearest post codes/outward codes, validation, or randomly generate a post code. API wrapper around <https://postcodes.io>.

This package provides convenience functions and pre-programmed Stan models related to the paired comparison factor model. Its purpose is to make fitting paired comparison data using Stan easy. This package is described in Pritikin (2020) <doi:10.1016/j.heliyon.2020.e04821>.

Transforms or simulates data with a target empirical covariance matrix supplied by the user. The method to obtain the data with the target empirical covariance matrix is described in Section 5.1 of Christidis, Van Aelst and Zamar (2019) <arXiv:1812.05678>.

This package provides delayed computation of a matrix of scaled and centered values. The result is equivalent to using the scale function but avoids explicit realization of a dense matrix during block processing. This permits greater efficiency in common operations, most notably matrix multiplication.

This package defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. It provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users.

mlr3learners extends mlr3 and mlr3proba with interfaces to essential machine learning packages on CRAN. This includes, but is not limited to: (penalized) linear and logistic regression, linear and quadratic discriminant analysis, k-nearest neighbors, naive Bayes, support vector machines, and gradient boosting.

This package draws protein schematics from Uniprot API output. From the JSON returned by the GET command, it creates a dataframe from the Uniprot Features API. This dataframe can then be used by geoms based on ggplot2 and base R to draw protein schematics.

GSALightning provides a fast implementation of permutation-based gene set analysis for two-sample problem. This package is particularly useful when testing simultaneously a large number of gene sets, or when a large number of permutations is necessary for more accurate p-values estimation.

This package provides a set of tools built around updateObject() to work with old serialized S4 instances. The package is primarily useful to package maintainers who want to update the serialized S4 instances included in their package. This is still work-in-progress.

The COVID Symptom Study is a non-commercial project that uses a free mobile app to facilitate real-time data collection of symptoms, exposures, and risk factors related to COVID19. The package allows easy access to summary statistics data from COVID Symptom Study Sweden.

Helper functions for descriptive tasks such as making print-friendly bivariate tables, sample size flow counts, and visualizing sample distributions. Also contains R approximations of some common SAS and Stata functions such as PROC MEANS from SAS and ladder', gladder', and pwcorr from Stata'.

Flexible implementation of a structural change point detection algorithm for multivariate time series. It authorizes inclusion of trends, exogenous variables, and break test on the intercept or on the full vector autoregression system. Bai, Lumsdaine, and Stock (1998) <doi:10.1111/1467-937X.00051>.

This package provides a suite of tools to allow you to download all publicly available parasite rate survey points, mosquito occurrence points and raster surfaces from the Malaria Atlas Project <https://malariaatlas.org/> servers as well as utility functions for plotting the downloaded data.

Transactions occurring for a UK-based and registered, non-store online retail between 01/12/2010 and 09/12/2011 (Chen et. al., 2012, <doi:10.1145/1835804.1835882>). This dataset is included in this package with the donor's permission, Dr. Daqing Chen.

This package provides function for performing Bayesian survival regression using Horseshoe prior in the accelerated failure time model with log normal assumption in order to achieve high dimensional pan-cancer variable selection as developed in Maity et. al. (2019) <doi:10.1111/biom.13132>.

Annotation files of the formatted genomic annotation for ChromHMM. Three types of text files are included the chromosome sizes, region coordinates and anchors specifying the transcription start and end sites. The package includes data for two versions of the genome of humans and mice.

Coordinate-based genomic visualization package for R. It grants users the ability to programmatically produce complex, multi-paneled figures. Tailored for genomics, plotgardener allows users to visualize large complex genomic datasets and provides exquisite control over how plots are placed and arranged on a page.

This package creates pre- and post- intervention scattergrams based on audiometric data. These scattergrams are formatted for publication in Otology & Neurotology and other otolaryngology journals. For more details, see Gurgel et al (2012) <doi:10.1177/0194599812458401>, Oghalai and Jackler (2016) <doi:10.1177/0194599816638314>.