Glymour / Scheines / Spirtes Discovering Causal Structure

Artificial Intelligence, Philosophy of Science, and Statistical Modeling
1. Auflage 2014
ISBN: 978-1-4832-6579-7
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 412 Seiten, Web PDF

Discovering Causal Structure: Artificial Intelligence, Philosophy of Science, and Statistical Modeling provides information pertinent to the fundamental aspects of a computer program called TETRAD. This book discusses the version of the TETRAD program, which is designed to assist in the search for causal explanations of statistical data. or alternative models. This text then examines the notion of applying artificial intelligence methods to problems of statistical model specification. Other chapters consider how the TETRAD program can help to find god alternative models where they exist, and how it can help detect the existence of important neglected variables. This book discusses as well the procedures for specifying a model or models to account for non-experimental or quasi-experimental data. The final chapter presents a description of the format of input files and a description of each command. This book is a valuable resource for social scientists and researchers.

Autoren/Hrsg.

Glymour, Clark

Scheines, Richard

Spirtes, Peter

Inhaltsverzeichnis

1;Front Cover
;1
2;Discovering Causal Structure: Artificial Intelligence, Philosophy of Science, and Statistical Modeling;4
3;Copyright Page
;5
4;Table of Contents
;8
5;Dedication;6
6;About This Book;12
7;Foreword;14
8;Acknowledgments;18
9;PART I: Artificial Intelligence and Nonexperimental Science;20
9.1;CHAPTER 1. THE PROBLEMS OF SCIENCE WITHOUT EXPERIMENTS;22
9.1.1;1.1. The Limits of Experimentation;22
9.1.2;1.2. The Limits of Human Judgment;23
9.1.3;1.3. The Artificial Intelligence Solution;30
9.2;CHAPTER 2. THE CASE AGAINST CAUSAL MODELING;34
9.2.1;2.1. The Critical Reaction;34
9.2.2;2.2. Making Sense of Causality;35
9.2.3;2.3. Causes, Indicators, and the Interpretation of Latent Variables;41
9.2.4;2.4. The Importance of Experiment;45
9.2.5;2.5. Justifying Assumptions;49
9.2.6;2.6. Linear Theories Are Literally False;50
9.2.7;2.7. Conclusion;58
9.3;CHAPTER 3. OBJECTIONS TO DISCOVERY BY COMPUTER;60
9.3.1;3.1. Introduction;60
9.3.2;3.2. The General Objections;61
9.3.3;3.3. No Peeking;64
10;PART II: The TETRAD Program;80
10.1;CHAPTER 4. CAUSAL AND STATISTICAL MODELS;81
10.1.1;4.1. Introduction;81
10.1.2;4.2. Directed Graphs and Causal Models;82
10.1.3;4.3. Statistical Models from Causal Models;86
10.1.4;4.4. Treks and Coordinating Path Effects;91
10.1.5;4.5. Constraints on Correlations;93
10.1.6;4.6. Correlated Errors are not Equivalent to Direct Effects;105
10.1.7;4.7. Statistical Issues, Briefly Considered;110
10.2;CHAPTER 5. THE STRUCTURE AND METHOD OF TETRAD;112
10.2.1;5.1. The Methodological Principles That Underlie TETRAD;112
10.2.2;5.2. How the Methodological Principles Are Realized in TETRAD;114
10.2.3;5.3. Search Strategies for Finding Good Causal Models;116
10.2.4;5.4. A Sketch of the TETRAD Program;117
10.2.5;5.5. How to Use TETRAD'S Output;127
10.2.6;5.6. TETRAD and Other Search Procedures;138
10.2.7;5.7. Future Developments;141
10.3;CHAPTER 6. WHAT TETRAD CAN DO;142
10.3.1;6.1. Alienation;142
10.3.2;6.2. A Problem Using Simulated Data;143
10.3.3;6.3. Causal Order from Correlations;146
10.3.4;6.4. Kohn's Study and Temporal Order among Interview Questions;151
10.4;CHAPTER 7. SIMULATION STUDIES;153
10.4.1;7.1. A Simulated Case;153
10.4.2;7.2. Distinguishing Correlation from Causation;158
10.4.3;7.3. Locating Connected Variables;161
10.5;CHAPTER 8. CASE STUDIES;166
10.5.1;8.1. Introduction;166
10.5.2;8.2. Industrial and Political Development;167
10.5.3;8.3. Measuring the Authoritarian Personality;183
10.5.4;8.4. Alternatives to Regression Models;192
10.5.5;8.5. Introducing Latent Variables: Longitudinal Data with SAT Scores;197
10.5.6;8.6. Roll Call Voting;203
10.5.7;8.7. The Effects of Summer Head Start;216
10.5.8;8.8. Achievement, Ability, and Approval;231
10.5.9;8.9. The Stability of Alienation;246
10.6;CHAPTER 9. A BRIEF HISTORY OF HEURISTIC SEARCH IN APPLIED STATISTICS;253
10.7;CHAPTER 10. MATHEMATICAL FOUNDATIONS;266
10.7.1;10.1. The Algorithm;266
10.7.2;10.2. Proofs of Correctness of the Algorithms Employed TETRAD;275
11;Part III: Using TETRAD, EQS and LISREL;332
11.1;CHAPTER 11. USING TETRAD WITH EQS AND LISREL;333
11.1.1;11.1. LISREL and Its Restrictions;333
11.1.2;11.2. Overcoming the Restrictions;337
11.1.3;11.3. EQS;343
11.2;CHAPTER 12. RUNNING TETRAD;346
11.2.1;12.1. Installing TETRAD;346
11.2.2;12.2. Entering and Exiting TETRAD;347
11.2.3;12.3. Getting Help;347
11.2.4;12.4. Input Files;347
11.2.5;12.5. Output Files;354
11.2.6;12.6. View and Edit;354
11.2.7;12.7. The Run Command and Menus;355
11.2.8;12.8. User Interrupts;360
11.2.9;12.9. Errors;360
11.2.10;12.10. TETRAD Commands;364
11.2.11;12.11. Running TETRAD in Batch Mode;366
11.2.12;12.12. List of Commands;366
11.2.13;12.13. Command Summaries;367
12;Appendix : The Grammar of the Input;393
13;About the Authors;396
14;References;397
15;Index;408