In strengejacke/ggeffects: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  dev = "png",
  fig.width = 7,
  fig.height = 3.5,
  message = FALSE, warning = FALSE)
options(width = 800)

The documentation of the ggeffects package, including many examples, is available online. Here you can find the content of the available documents. Click on a link to visit the related website.

General introductions into the ggeffects package

• Adjusted Predictions of Regression Models
• Adjusted Predictions at Specific Values
• Adjusted Predictions for Random Effects Models
• (Cluster) Robust Standard Errors

Interpretation and Significance Testing

• Contrasts and Pairwise Comparisons
• Floodlight and Spotlight Analysis (Johnson-Neyman Intervals)
• Contrasts and Pairwise Comparisons for GLM
• Contrasts and Pairwise Comparisons for Zero-Inflation Models
• Different Backends for Pairwise Comparisons
• Adding Partial Residuals to Effects Plots

Creating and customizing plots and tables

• Plotting Adjusted Predictions
• Customize Plot Appearance
• Customize Table Appearance

Case Studies

• Simple Workflow using Logistic Regression
• Logistic Mixed Effects Model with Interaction Term
• Intersectionality Analysis using the MAIHDA Framework
• Comparison of ggeffects and marginaleffects

Technical details

• Adding own class-methods to ggeffects
• Difference between Marginalization Methods
• Different Output between Stata and ggeffects

strengejacke/ggeffects documentation built on Dec. 24, 2024, 3:27 a.m.