Multivariate Regression3 months ago
Preliminaries | Basic Usage | Example 1: Unadjusted Analysis | Example 2: Adjusted Analysis | Example 3: Unadjusted and Adjusted Comparison | Predictor Types | Example 4: Continuous Predictors | Example 5: Multilevel Categorical Predictors | Model Types | Example 6: Cox Regression | Example 7: Linear Regression | Example 8: Mixed-Effects Models | Advanced Features | Example 9: Interaction Terms | Example 10: Filtering by p-value | Example 11: Accessing Model Objects | Forest Plot Visualization | Example 12: Forest Plot for Logistic (Binary) Outcomes | Example 13: Customization Options | Example 14: Forest Plot for Continuous Outcomes | Example 15: Forest Plot for Survival Outcomes | Exporting Results | Tables | Forest Plots | Complete Workflow Example | Parameter Reference | Best Practices | Outcome Selection | Adjustment Strategy | Interpretation | Common Issues | Empty Results | Convergence Warnings | Varying Sample Sizes | Many Factor Levels | Other Considerations | Multivariate Regression vs. Univariable Screening | Categorical Outcomes with More Than Two Levels | Further Reading
summata 0.13.0Paul Hsin-ti McClelland multivariate_regression.Rmd