Computational tools for meta-analysis of diagnostic accuracy test. Bootstrap-based computational methods of the confidence interval for AUC of summary ROC curve and some related AUC-based inference methods are available (Noma et al. (2021) <doi:10.1080/23737484.2021.1894408>).

The deltaPlotR package implements Angoff's Delta Plot method to detect dichotomous DIF. Several detection thresholds are included, either from multivariate normality assumption or by prior determination. Item purification is supported (Magis and Facon (2014) <doi:10.18637/jss.v059.c01>).

This package provides a set of extensions for the ergm package to fit weighted networks whose edge weights are counts. See Krivitsky (2012) <doi:10.1214/12-EJS696> and Krivitsky, Hunter, Morris, and Klumb (2023) <doi:10.18637/jss.v105.i06>.

Quickly make tables of descriptive statistics (i.e., counts, percentages, confidence intervals) for categorical variables. This package is designed to work in a Tidyverse pipeline, and consideration has been given to get results from R to Microsoft Word ® with minimal pain.

This package provides a collection of functions for testing various aspects of univariate time series including independence and neglected nonlinearities. Further provides functions to investigate the chaotic behavior of time series processes and to simulate different types of chaotic time series maps.

Reads corporate data such as board composition and compensation for companies traded at B3, the Brazilian exchange <https://www.b3.com.br/>. All data is downloaded and imported from the ftp site <https://dados.cvm.gov.br/dados/CIA_ABERTA/DOC/FRE/>.

This package provides extensions for various geographic spatial file formats, such as shape files and rasters. Currently provides support for the terra geographic spatial formats. See the vignettes for worked examples, demonstrations, and explanations of how to use the various package extensions.

This package provides the OpenEXR static library and C++ headers for high-dynamic-range image I/O (see <https://openexr.com/>) needed to link R packages against the OpenEXR library, along with a basic R interface to load EXR images.

Error in a binary dependent variable, also known as misclassification, has not drawn much attention in psychology. Ignoring misclassification in logistic regression can result in misleading parameter estimates and statistical inference. This package conducts logistic regression analysis with misspecification in outcome variables.

Quickly make tables of descriptive statistics (i.e., counts, means, confidence intervals) for continuous variables. This package is designed to work in a Tidyverse pipeline, and consideration has been given to get results from R to Microsoft Word ® with minimal pain.

This package provides probability mass, distribution, quantile, random variate generation, and method-of-moments parameter fitting for the MBBEFD family of distributions used in insurance modeling as described in Bernegger (1997) <doi:10.2143/AST.27.1.563208> without any external dependencies.

This package implements two methods: a nonparametric risk adjustment and a data imputation method that use general population mortality tables to allow a correct analysis of time to disease recurrence. Also includes a powerful set of object oriented survival data simulation functions.

Simulates pooled sequencing data under a variety of conditions. Also allows for the evaluation of the average absolute difference between allele frequencies computed from genotypes and those computed from pooled data. Carvalho et al., (2022) <doi:10.1101/2023.01.20.524733>.

Fit a model with potentially many linear and smooth predictors. Interaction effects can also be quantified. Variable selection is done using penalisation. For l1-type penalties we use iterative steps alternating between using linear predictors (lasso) and smooth predictors (generalised additive model).

Computes sample size for Student's t-test and for the Wilcoxon-Mann-Whitney test for categorical data. The t-test function allows paired and unpaired (balanced / unbalanced) designs as well as homogeneous and heterogeneous variances. The Wilcoxon function allows for ties.

For Multi Parent Populations (MPP) Identity By Descend (IBD) probabilities are computed using Hidden Markov Models. These probabilities are then used in a mixed model approach for QTL Mapping as described in Li et al. (<doi:10.1007/s00122-021-03919-7>).

This package provides a set of segregation-based indices and randomization methods to make robust environmental inequality assessments, as described in Schaeffer and Tivadar (2019) "Measuring Environmental Inequalities: Insights from the Residential Segregation Literature" <doi:10.1016/j.ecolecon.2019.05.009>.

This package performs the Scott & Knott (1974) clustering algorithm as a multiple comparison method in the Analysis of Variance context, for both balanced and unbalanced <doi:10.1590/1984-70332017v17n1a1> designs. Accepts input from formula', aov', lm', aovlist', and lmerMod objects.

This package provides a framework for modeling cellular metabolic states and continuous metabolic trajectories from single-cell RNA-seq data using pathway-level scoring. Enables lineage-restricted metabolic analysis, metabolic pseudotime inference, module-level trend analysis, and visualization of metabolic state transitions.

Wavelet routines that calculate single sets of wavelet multiple regressions and correlations, and cross-regressions and cross-correlations from a multivariate time series. Dynamic versions of the routines allow the wavelet local multiple (cross-)regressions and (cross-)correlations to evolve over time.

An all-in-one document reader for GNU Emacs, supporting all major document formats. This package intends to take from doc-view, nov.el, and pdf-tools and make them better. And as such, it is effectively a drop-in replacement for them.

This package provides the output of running Salmon on a set of 24 RNA-seq samples from Alasoo, et al. "Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response", published in Nature Genetics, January 2018.

The R package data.table is an extension of data.frame providing functions for fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group, column listing and fast file reading.

This package provides iterative methods for matrix completion that use nuclear-norm regularization. The package includes procedures for centering and scaling rows, columns or both, and for computing low-rank single value decompositions (SVDs) on large sparse centered matrices (i.e. principal components).