rigr-package: Regression, Inference, and General Data Analysis Tools in R

In rigr: Regression, Inference, and General Data Analysis Tools in R

Regression, Inference, and General Data Analysis Tools in R

Description

Developed by Scott S. Emerson, Andrew J. Spieker, Brian D. Williamson, and Travis Y. Hee Wai at the University of Washington Department of Biostatistics. Currently maintained by Prof. Amy Willis at the University of Washington Department of Biostatistics. Previously maintained by Charles Wolock and Taylor Okonek, also at the University of Washington Department of Biostatistics. Aims to facilitate regression, descriptive statistics, and one- and two-sample inference by implementing more intuitive layout and functionality for existing R functions.

Details

Package:	rigr
Type:	Package
Version:	1.0.0
Date:	2021-09-10
License:	MIT

A set of tools designed to facilitate easy adoption of R for students in introductory classes with little programming experience. Compiles output from existing routines together in an intuitive format, and adds functionality to existing functions. For instance, the regression function can perform linear models and generalized linear models. The user can also specify multiple-partial F-tests to print out with the model coefficients, and robust standard errors are provided automatically. We also provide functions for descriptive statistics and one- and two-sample inference with improved, legible output.

Author(s)

Scott S. Emerson, Andrew J. Spieker, Brian D. Williamson, Amy D. Willis, Charles Wolock, and Taylor Okonek

Maintainer: Amy Willis <[e-mail]>

rigr documentation built on Sept. 7, 2022, 1:05 a.m.