Quantitative Models in Psychology

Training in quantitative methods primarily involves studying the mechanics of statistics or, in other words, the "how" of data analysis. What is less studied is the "why," or the foundational theory underlying these concepts. Using the organizing principle that quantitative methods are the building blocks of models, this book focuses on models of inference, models of measurement, and the modeling of psychological phenomena. With clear prose and a reader-friendly format, McGrath introduces a conceptual framework for the entire spectrum of quantitative modeling procedures used in psychology while providing a solid grounding in its methods and practices. The result is a comprehensive survey of quantitative methods and concepts in psychology that covers everything needed at the graduate level and beyond, including generalizing from samples to populations, using measurement instruments to generate quantitative scales, and modeling real-world patterns and relationships. This book presents the most important and practically relevant quantitative models for the behavioral and social sciences and encourages psychologists and graduate students to think critically about the limitations of the methods currently in use.

Robert E. McGrath, PhD, is a professor of psychology at Fairleigh Dickinson University, where he currently directs both the doctoral program in clinical psychology and the master of science program in clinical psychopharmacology.

He received his doctorate in clinical psychology in 1984 from Auburn University. He has since authored approximately 150 publications and presentations, primarily in the areas of assessment and measurement, statistical methodology, and professional issues in pharmacotherapy.

Dr. McGrath has been a candidate for president of APA, served on the APA Division 12 (Society of Clinical Psychology) Committee on Science and Practice, and is a former president of APA Division 55 (American Society for the Advancement of Pharmacotherapy).

He is the three-time winner of the Martin Mayman Award presented by the Society for Personality Assessment for contributions to the literature on personality assessment.

Preface	p. ix
Introduction	p. 3
Quantitative Models in Psychology	p. 4
Are Models Always Realistic?	p. 5
This Book	p. 6
Models of Inference	p. 11
Preliminary Concepts in Inference	p. 13
The Problem of Error	p. 14
Binomial Distributions	p. 16
The Sampling Distribution of the Mean	p. 22
The t Distribution	p. 29
Conclusion	p. 33
Significance Testing	p. 35
Fisher's Model	p. 36
Fleshing Out the Model	p. 39
The Good, the Bad, and the Alternative	p. 54
Conclusion	p. 55
Null Hypothesis Significance Testing	p. 57
The Decision Matrix	p. 57
Controlling the Outcomes	p. 61
The Good, the Bad, and the Alternative	p. 69
Conclusion	p. 72
Practical Issues in Null Hypothesis Significance Testing	p. 73
Practical Power Analysis	p. 75
The Significance Testing Controversy	p. 79
Living With Significance Tests	p. 83
Conclusion	p. 89
Alternatives to Null Hypothesis Significance Testing	p. 91
Interval Estimation	p. 92
Meta-Analysis	p. 99
Bayesian Methods	p. 107
Conclusion	p. 121
Models of Measurement	p. 123
Models of Measurement Error	p. 125
True-Score Theory	p. 126
Validity Theory	p. 140
Conclusion	p. 148
Latent-Variable Models	p. 149
Factor Analysis	p. 152
Structural Equation Modeling	p. 163
Item Response Theory	p. 164
Categorical Latent-Variable Models	p. 170
Conclusion	p. 174
Structural Modeling	p. 177
Preliminary Concepts in Structural Modeling	p. 179
Formal Classification of Variables	p. 180
Practical Classification of Variables	p. 185
Exploratory Versus Confirmatory Modeling	p. 188
Conclusion	p. 189
Modeling Psychological Phenomena	p. 191
Modeling Variable Distributions	p. 192
Modeling Two-Variable Relationships	p. 194
Modeling Relationships With Three or More Variables	p. 199
Conclusion	p. 216
References	p. 217
Index	p. 231
About The Author	p. 241
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Quantitative Models in Psychology

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