Ebook: Structural Equations with Latent Variables

Analysis of Ordinal Categorical Data Alan Agresti Statistical Science Now has its first coordinated manual of methods for analyzing ordered categorical data. This book discusses specialized models that, unlike standard methods underlying nominal categorical data, efficiently use the information on ordering. It begins with an introduction to basic descriptive and inferential methods for categorical data, and then gives thorough coverage of the most current developments, such as loglinear and logit models for ordinal data. Special emphasis is placed on interpretation and application of methods a.;Title Page; Dedication; Copyright; Preface; CHAPTER ONE: Introduction; HISTORICAL BACKGROUND; CHAPTER TWO: Model Notation, Covariances, and Path Analysis; MODEL NOTATION; COVARIANCE; PATH ANALYSIS; SUMMARY; CHAPTER THREE: Causality and Causal Models; NATURE OF CAUSALITY; ISOLATION; ASSOCIATION; DIRECTION OF CAUSATION; LIMITATIONS OF "CAUSAL" MODELING; SUMMARY; CHAPTER FOUR: Structural Equation Models with Observed Variables; MODEL SPECIFICATION; IMPLIED COVARIANCE MATRIX; IDENTIFICATION; ESTIMATION; FURTHER TOPICS; SUMMARY; APPENDIX 4A DERIVATION OF FML (y and x MULTINORMAL).