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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
1.0
Administration
Up to Scratch
3
2.1
Notebook – Introduction
2.2
Notebook – Linear Models
2.3
Notebook – Intro to R
Intro to GLMs
4
3.1
Linear Models vs. Generalized Linear Models
3.2
Least Squares vs. Maximum Likelihood
3.3
Saturated vs. Constrained Model
3.4
Link Functions
Exponential Family
5
4.0
Definition and Examples
4.1
More Examples
4.2
Notebook – Exponential Family
4.3
Mean and Variance
4.4
Notebook – Mean-Variance Relationship
Deviance
2
5.0
Deviance
5.1
Notebook – Deviance
Likelihood Analysis
5
6.1
Likelihood Analysis
6.2
Numerical Solution
6.3
Notebook – GLM’s in R
6.4
Notebook – Fitting the GLM
6.5
Inference
Code Examples
3
7.0
Notebook – Binary/Binomial Regression
7.1
Notebook – Poisson & Negative Binomial Regression
7.2
Notebook – Gamma & Inverse Gaussian Regression
Advanced Topics
4
8.0
Quasi-Likelihood
8.1
Generalized Estimating Equations – GEE
8.2
Mixed Models – GLMM
8.3
Regular vs. Mixed Models – 2 Examples
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