Frequentist mixed models: Inference and model selection

Introduction

What this guide covers

Introduction Mathematical statistics and asymptotic theory

Overview

Topics covered

• Introduction
• Frequentist Mixed Models: Inference and Selection
• General Mathematical Formalization of Mixed Models
• 1.1 Conditional and Marginal Distributions
• Parameter Estimation: Maximum Likelihood (ML) vs. Restricted Maximum Likelihood (REML)
• 2.1 ML Log-Likelihood Function

Related concepts

Main connections

• Maximum likelihood estimation
• Mixed & multilevel models (GLMM)
• Variance & standard deviation
• Linear algebra & matrices
• Calculus & differentiation
• Residual analysis & diagnostics

Compatible notation

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