Statistical Modeling & Regression · Categorical Data Analysis

Categorical data analysis · Log-linear models for contingency tables

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Introduction Advanced Multivariate Analysis · Loglinear Models

Overview

Topics covered

  • Introduction
  • Loglinear Models for Contingency Tables
  • Introduction and Fundamentals of Categorical Data
  • 1. Poisson Sampling Scheme
  • 2. Multinomial Sampling Scheme
  • 3. Multinomial Product Sampling Scheme

Related concepts

Main connections

  • Maximum likelihood estimation
  • Conditional probability & independence
  • Poisson distribution
  • Linear algebra & matrices
  • Epidemiological measures & risk ratios
  • Residual analysis & diagnostics

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

ℙ(𝐘=𝐲)=∏i=1Ne−μiμiyiyi!,yi∈ℕ0.
View LaTeX source\P(\mathbf{Y} = \mathbf{y}) = \prod_{i=1}^N \frac{e^{-\mu_i} \mu_i^{y_i}}{y_i!}, \qquad y_i \in \N_0.