Linear Models

  1. Extensions and Advanced Topics
    1. Generalized Linear Models
      1. Components of GLMs
        1. Random Component
          1. Exponential Family Distributions
          2. Systematic Component
            1. Linear Predictor
          3. Logistic Regression
            1. Model Formulation
              1. Interpretation of Coefficients
                1. Odds and Odds Ratios
                2. Poisson Regression
                  1. Model Formulation
                    1. Interpretation of Coefficients
                      1. Rate Interpretation
                    2. Mixed-Effects Models
                      1. Fixed vs. Random Effects
                        1. Definition of Fixed Effects
                          1. Definition of Random Effects
                          2. Hierarchical Data Structures
                            1. Nested Data
                              1. Random Intercepts and Slopes
                            2. Regularization Methods
                              1. Ridge Regression
                                1. L2 Penalty
                                  1. Effect on Coefficient Estimates
                                  2. Lasso Regression
                                    1. L1 Penalty
                                      1. Variable Selection Property
                                      2. Elastic Net
                                        1. Combined L1 and L2 Penalties
                                          1. Advantages and Use Cases

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                                      6. Model Building and Variable Selection

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                                      1. Introduction to Linear Relationships