Presenting Statistical Results Effectively
Association Function
Bootstrap Importance Function
Caption Grob
Compact Letter Display for Simple Slopes
Hybrid Plot for DFBETAS
Heatmap Fit Plot using GGplot
Importace Measure for Generalized Linear Models
Dot Plot with Letter Display
Make Arguments for Linear Smooth
Make Arguments for LOESS Smooth
Linear Scatterplot Array
Kernel Density with Normal Density Overlay
Calculate the Optimal Visual Testing Confidence Level
Print Method for Silber, Rosenbaum and Ross Importance Measure
Print Method for Simple Slopes
Quantile Comparison Data
Residual-Residual Plot
Shuffle coefficients and standard errors together
Calculate Simple Slopes
Absolute Importance Measure
Truncated Power Basis Functions
Transform Variables to Normality
Includes functions and data used in the book "Presenting Statistical Results Effectively", Andersen and Armstrong (2022, ISBN: 978-1446269800). Several functions aid in data visualization - creating compact letter displays for simple slopes, kernel density estimates with normal density overlay. Other functions aid in post-model evaluation heatmap fit statistics for binary predictors, several variable importance measures, compact letter displays and simple-slope calculation. Finally, the package makes available the example datasets used in the book.