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Generalized Linear Models with R
Generalized Linear Models with R
Curriculum
8 Sections
27 Lessons
Lifetime
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Admministration
1
1.1
Administration
Up to Scratch
3
2.2
Notebook – Introduction
2.3
Notebook – Linear Models
2.4
Notebook – Intro to R
Intro to GLMs
4
3.2
Linear Models vs. Generalized Linear Models
3.3
Least Squares vs. Maximum Likelihood
3.4
Saturated vs. Constrained Model
3.5
Link Functions
Exponential Family
5
4.1
Definition and Examples
4.2
More Examples
4.3
Notebook – Exponential Family
4.4
Mean and Variance
4.5
Notebook – Mean-Variance Relationship
Deviance
2
5.1
Deviance
5.2
Notebook – Deviance
Likelihood Analysis
5
6.2
Likelihood Analysis
6.3
Numerical Solution
6.4
Notebook – GLM’s in R
6.5
Notebook – Fitting the GLM
6.6
Inference
Code Examples
3
7.1
Notebook – Binary/Binomial Regression
7.2
Notebook – Poisson & Negative Binomial Regression
7.3
Notebook – Gamma & Inverse Gaussian Regression
Advanced Topics
4
8.1
Quasi-Likelihood
8.2
Generalized Estimating Equations – GEE
8.3
Mixed Models – GLMM
8.4
Regular vs. Mixed Models – 2 Examples
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