GLM - Multinomial Regression (1/3) - Intro

In this video we will look into multinomial regression, and give an introduction to the topic, including a reminder of the categorical and multinomial distributions. In the next two videos we'll go in depth to the two types of models used for nominal and ordinal response (y) data.
Alan Agresti's Book: shorturl.at/aHY79
Gordon Smyth's paper: gksmyth.github.io/pubs/edm-gn...
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“GLM in R” Course Outline:
Administration
* Administration
Up to Scratch
* Notebook - Introduction
* Notebook - Linear Models
* Notebook - Intro to R
Intro to GLM’s
* Linear Models vs. Generalized Linear Models
* Least Squares vs. Maximum Likelihood
* Saturated vs. Constrained Model
* Link Functions
Exponential Family
* Definition and Examples
* More Examples
* Notebook - Exponential Family
* Mean and Variance
* Notebook - Mean-Variance Relationship
Deviance
* Deviance
* Notebook - Deviance
Likelihood Analysis
* Likelihood Analysis
* Numerical Solution
* Notebook - GLM’s in R
* Notebook - Fitting the GLM
* Inference
Code Examples:
* Notebook - Binary/Binomial Regression
* Notebook - Poisson & Negative Binomial Regression
* Notebook - Gamma & Inverse Gaussian Regression
Advanced Topics:
* Quasi-Likelihood
* Generalized Estimating Equations (GEE)
* Mixed Models (GLMM)
* Regular vs. Mixed Models
Multinomial Regression
* Intro
* Nominal Data - Baseline Category
* Ordinal Data - Cumulative Link
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[@includestdio.h8492]

Thank u so much!

[@aza6513]

Wow, will you cover nested logit model? And relationship with gev or vglm