Regression, Inference, and General Data Analysis Tools in R
ANOVA
Calculate Cook's distances from uRegress objects
Descriptive Statistics
Calculate dfbeta from uRegress objects
Calculate dfbetas from uRegress objects
Create Dummy Variables
Calculate the hat-values (leverages) from uRegress objects
Tests of Linear Combinations of Regression Coefficients
Create Polynomials
Prediction Intervals for uRegress objects
Test of proportions with improved layout
Test of proportions from summary statistics
General Regression for an Arbitrary Functional
Extract Residuals from uRegress objects
Regression, Inference, and General Data Analysis Tools in R
Extract standardized residuals from uRegress objects
Extract Studentized residuals from uRegress objects
T-test with Improved Layout
T-test Given Summary Statistics with Improved Layout
Create a Partial Formula
Wilcoxon Signed Rank and Mann-Whitney-Wilcoxon Rank Sum Test
A set of tools to streamline data analysis. Learning both R and introductory statistics at the same time can be challenging, and so we created 'rigr' to facilitate common data analysis tasks and enable learners to focus on statistical concepts. We provide easy-to-use interfaces for descriptive statistics, one- and two-sample inference, and regression analyses. 'rigr' output includes key information while omitting unnecessary details that can be confusing to beginners. Heteroscedasticity-robust ("sandwich") standard errors are returned by default, and multiple partial F-tests and tests for contrasts are easy to specify. A single regression function can fit both linear and generalized linear models, allowing students to more easily make connections between different classes of models.