Categorical data analysis: Introduction to generalized linear models (GLM)

Introduction

What this guide covers

Introduction Introduction Advanced inference and modeling theory

Overview

Topics covered

• Introduction
• Categorical Data Analysis and Introduction to MGL
• Limitations of the Classical Linear Model (MLC)
• The Linear Probability Model (MLP) and its structural flaws
• Count data and the breakdown of the constant variance hypothesis
• Structure of the Exponential Family of Distributions

Related concepts

Main connections

• Logistic regression
• Maximum likelihood estimation
• Variance & standard deviation
• Poisson distribution
• Residual analysis & diagnostics
• Binomial distribution

Compatible notation

Mathematical sample in LaTeX

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