Theory Construction and Model-Building Skills

A Practical Guide for Social Scientists

James Jaccard and Jacob Jacoby

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December 22, 2009
ISBN 9781606233405
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391 Pages
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391 Pages
Size: 7" x 10"
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391 Pages
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Meeting a crucial need for graduate students and newly minted researchers, this innovative text provides hands-on tools for generating ideas and translating them into formal theories. It is illustrated with numerous practical examples drawn from multiple social science disciplines and research settings. The authors offer clear guidance for defining constructs, thinking through relationships and processes that link constructs, and deriving new theoretical models (or building on existing ones) based on those relationships. Step by step, they show readers how to use causal analysis, mathematical modeling, simulations, and grounded and emergent approaches to theory construction. A chapter on writing about theories contains invaluable advice on crafting effective papers and grant applications.

Useful pedagogical features in every chapter include:

This title is part of the Methodology in the Social Sciences Series, edited by Todd D. Little, PhD.

“This book is aimed to provide social scientists with hand-on tools for defining concepts and formalizing theories. It is particularly addressed to graduate students and it ranges from causal analysis to mathematical modeling, from simulation to grounded and emergent approaches to theory construction. It is well organized, includes many simple and effective examples, and has a very clear setup. At the end of each chapter, the authors provide a summary, concluding comments, and suggested readings. The latter are complemented by a sentence about the content of each referenced literature, which is very helpful to find the respective reference of interest. Above, an index with key terms of each chapter and intuitive exercises to deepen the understanding of it are provided. Doing so, the book is very suitable for didactical purpose, in particular for research courses to graduate students. The effective, easy-to-understand, and straightforward style of writing is noticeable since from the first pages of the book....The book is highly recommendable for social science students, is a good lecture for young and open minded researchers, and locates simulation at the core of the scientific endeavour.”

Journal of Artificial Societies and Social Stimulation

“This much-needed book fills a gap in the social science literature. The text provides clear examples of how researchers and graduate students can formulate conceptual models, grapple with issues of measurement, and choose the most appropriate data-analytic methods for their conceptual frameworks. The authors have done an exceptional job of providing detailed instruction in the formulation and development of strong theories of behavior. Jaccard and Jacoby have written a high-quality, clear, and useful text. I highly recommend this text for graduate-level research courses and for applied researchers focused on the development of rigorous theoretical frameworks.”

—Vincent Guilamo-Ramos, PhD, LCSW, Columbia University School of Social Work

“I know of no better introduction to theory development and hypothesis testing in the social sciences. Jaccard and Jacoby pull off an impressive high-wire act: they explore the conceptual underpinnings of science while providing lots of good, practical advice; they cover a wide range of approaches while avoiding oversimplification; and they offer an epistemologically principled yet inclusive vision of what social science is and could be.”

—Philip E. Tetlock, PhD, Mitchell Endowed Chair, Haas School of Business, University of California, Berkeley

“Too often, students just study the writings and theories of others, and are left on their own when it comes to developing theory directly relevant to their research problems. Jaccard and Jacoby have written a wonderful, practical guide to help budding and experienced social scientists do just that. The book is clearly written and well organized. It would make an excellent text for graduate students from a variety of social science fields.”

—Kenneth A. Bollen, PhD, H. R. Immerwahr Distinguished Professor of Sociology and Director, Howard W. Odum Institute for Research in Social Science, University of North Carolina at Chapel Hill

“Filling an important gap, this book is very well written and impressive in its coverage. It is the perfect text for early-career graduate students in sociology, organizational studies, education, and psychology. I highly recommend it for graduate-level courses such as Research Methods, The Nature of Scientific Inquiry, and Research Practicum, and I will use it with my graduate students.”

—Elif Andac, PhD, Department of Sociology, University of Kansas

“Outstanding. The authors explain abstract ideas in impressively straightforward and understandable language, and the self-study materials at the end of each chapter are well formulated. I urge any scientist who is designing a program of research to spend some time using the tools in this book.”

—Thomas A. Cornille, PhD, Department of Family and Child Sciences, Florida State University

“An excellent book on how to develop theory in the social sciences. It is mainly oriented toward quantitative reasoning and models, but there are valuable ideas and strategies for qualitative research as well. It is very readable and contains helpful exercises and examples.”

—Joseph Maxwell, PhD, Graduate School of Education, George Mason University

“This book's pages will become worn and tattered as graduate students, professors, and researchers across the social sciences refer to it repeatedly to inform their efforts to do theoretically engaged empirical research.”

—Richard Tardanico, PhD, Chair, Department of Sociology and Anthropology, Florida International University

“This book will help you think about the work you do in a different way. It will tighten up your own thinking as well as how you present your theoretical models to others. It will enable you to write better grant proposals, and could help make the difference between a fundable score and a nonfundable score.”

—Rob Turrisi, PhD, Department of Biobehavioral Health, Pennsylvania State University

Table of Contents


1. Introduction

Organization of the Book

Theories and Settings

2. The Nature of Understanding

The Nature of Reality

How Reality Is Experienced

Concepts: The Building Blocks of Understanding

The Nature of Concepts

Concepts, Constructs, and Variables

Conceptual Systems: The Bases for Deeper Understanding


Summary and Concluding Comments

Suggested Readings

Key Terms


3. Science as an Approach to Understanding

Socially Based Approaches to Understanding

Commonalities across All Shared Conceptual Approaches

Special Features of the Scientific Approach

The Essentials of Scientific Endeavor

The Process of Theory Construction

What Is a Theory?

Theories, Models, and Hypotheses

Types of Theories

The Role of Theory in Basic versus Applied Research

Characteristics of a Good Theory

Science and Objectivity

Summary and Concluding Comments

Suggested Readings

Key Terms


II. Core Processes

4. Creativity and the Generation of Ideas


One Small Step for Science


The Creative Person

Creative Ideas

The Creative Process

Deciding to Be Creative

Practical Implications for Theory Construction

Choosing What to Theorize About

Literature Reviews

Heuristics for Generating Ideas

Idea Generation and Grounded/Emergent Theorizing

Twenty-Six Heuristics

When the Focus Is on Basic Mental or Biological Processes

Scientists on Scientific Theorizing

Summary and Concluding Comments

Suggested Readings

Key Terms


5. Focusing Concepts

The Process of Instantiation

The Nature of Conceptual Definitions

Shared Meaning, Surplus Meaning, and Nomological Networks

Practical Strategies for Specifying Conceptual Definitions

Multidimensional Constructs

Creating Constructs

An Example of Specifying Conceptual Definitions


Summary and Concluding Comments

Suggested Readings

Key Terms


6. Clarifying Relationships Using Thought Experiments

Thought Experiments for Relationships in Grounded and Emergent Theory

Describing Relationships with Different Types of Variables

Thought Experiments for Relationships between Categorical Variables

Categorical Variables with Two Levels

Categorical Variables with More Than Two Levels

Thought Experiments for Relationships between Quantitative Variables


Characteristics of Linear Relationships

Nonlinear Relationships

When Nonlinear Relationships Are Linear

A Thought Experiment with Hypothetical Scatterplots

Thought Experiments for Relationships between Categorical and Quantitative Variables

Thought Experiments for a Categorical Cause and a Quantitative Effect: The Use of Hypothetical Means

Thought Experiments for a Quantitative Cause and a Categorical Effect: The Use of Hypothetical Probabilities

Thought Experiments for Moderated Relationships

Thought Experiments Using Hypothetical Factorial Designs

Hypothetical Factorial Designs with More Than Two Levels

Hypothetical Factorial Designs with Quantitative Variables

Hypothetical Scatterplots and Quantitative Variables

Summary for Moderated Relationships

Broader Uses of Hypothetical Factorial Designs in Thought Experiments

Relationships Characterized by Main Effects

Relationships Characterized by Simple Main Effects

Relationships Characterized by Interaction Contrasts

Choice of the Moderator Variable

Summary and Concluding Comments

Suggested Readings

Key Terms


APPENDIX 6A. Thought Experiments for a Quantitative Cause and Categorical Effect: A Hypothetical Contingency Table Method

APPENDIX 6B. Thought Experiments for Moderated Moderation

III. Frameworks for Theory Construction

7. Causal Models

Two Types of Relationships: Predictive and Causal

Predictive Relationships

Causal Relationships

Causality and Grounded/Emergent Theory

Types of Causal Relationships

Constructing Theories with Causal Relationships

Identifying Outcome Variables

Identifying Direct Causes

Indirect Causal Relationships

Turning Direct Relationships into Indirect Relationships

Partial Mediation versus Complete Mediation

An Alternative Strategy for Turning Direct Effects into Indirect Effects

The Essence of Mediation

Moderated Causal Relationships

Mediated Moderation

Moderated Mediation

Moderated Moderation

Summary of Moderated Relationships

Reciprocal or Bidirectional Causality

There Is No Such Thing as Simultaneous Reciprocal Causality

Feedback Loops: Adding Mediators to Reciprocal Causation

Moderated Reciprocal Causation

Spurious Relationships

Adding Additional Outcomes

Adding Effects of Effects

Specifying Causal Relationships between Existing Variables

Summary of Additional Steps That May Create Spuriousness

Unanalyzed Relationships

Expanding the Theory Further

Temporal Dynamics

Disturbance Terms

Latent Variables, Structural Theory, and Measurement Theory

Revisiting Your Literature Review

Some Final Steps

Perspectives on the Construction of Causal Theories

Path Diagrams as Theoretical Propositions

A Note on Research Design and Statistical Analysis

Elaborating the Logic Underlying Each Path

The Use of Causal Analysis in Grounded/Emergent Theorizing

Summary and Concluding Comments

Suggested Readings

Key Terms


8. Mathematical Models

Types of Variables: Categorical, Discrete, and Continuous

Axioms and Theorems


Linear Functions

The Slope and Intercept

Deterministic versus Stochastic Models

Model Parameters

Adjustable Parameters and Parameter Estimation

Rates and Change: Derivatives and Differentiation

Instantaneous Change

Second and Third Derivatives

Describing Accumulation: Integrals and Integration

Just-Identified, Overidentified, and Underidentified Models


Types of Nonlinearity

Logarithmic Functions

Exponential Functions

Power Functions

Polynomial Functions

Trigonomic Functions

Choosing a Function

Functions for Categorical Variables

Advanced Topics: Manipulating and Combining Functions

Function Transformations

Combining Functions

Multiple Variable Functions

Phases in Building a Mathematical Model

An Example Using Performance, Ability, and Motivation

An Example Using Cognitive Algebra

An Example Using Attitude Change

An Example Using a Traditional Causal Model

Chaos Theory

Catastrophe Theory

Additional Examples of Mathematical Models in the Social Sciences

Emergent Theory Construction and Mathematical Models

Summary and Concluding Comments

APPENDIX 8A. SPSS Code for Exploring Distribution Properties

APPENDIX 8B. Additional Modeling Issues for the Performance, Motivation, and Ability Example

Suggested Readings

Key Terms


9. Simulation as a Theory Development Method

Defining Simulations

The Uses of Research Simulations

The Difference between Simulation and Laboratory Experiments

Basic Simulation Varieties

All-Machine versus Person–Machine Simulations

Descriptive versus Analytic Simulations

Real-Time versus Compressed-Time versus Expanded-Time Simulations

Deterministic versus Nondeterministic Simulations

Free versus Experimental Simulations

Macro- versus Microsimulations

Content-Oriented Simulation

The Analysis of Criterion Systems as a Basis for Theory Construction

Simulation of Information Accessing in Consumer Purchase Decisions

Virtual Environments and Avatars

Simulations and Virtual Experiments

Agent-Based Modeling

Resources for Conducting Simulations

Summary and Concluding Comments

Suggested Readings

Key Terms


10. Grounded and Emergent Theory

Grounded and Emergent Theory: An Overview

Positivism "versus" Constructivism

Framing the Problem

The Role of Past Literature

Collecting Qualitative Data

Archival Records

Direct Observation

Structured and Unstructured Interviews and Surveys

Focus Groups

Virtual Ethnographies

Directive Qualitative Methods

Mixed-Methods Research

Memo Writing

Theoretical Sampling

Analyzing and Coding Data

An Example from Anthropology

The Statistical Exploration of Relationships

Process Analysis in Emergent Theorizing

Moving to Theoretical Statements: Using Principles of Rhetoric

Deduction, Induction, and Abduction

Toulmin's Model of Argumentation

Weak Arguments

APPENDIX 10A. The Limits of Information Processing

Summary and Concluding Comments

Suggested Readings

Key Terms


11. Historically Influential Systems of Thought

Grand Theories




Symbolic Interactionism

Evolutionary Perspectives

Postmodernism: A Critical Commentary on Grand Theories

Frameworks Using Metaphors

Neural Networks

Systems Theory

Frameworks Emphasizing Stability and Change

Psychological Frameworks

Reinforcement Theories

Humanism and Positive Psychology

Frameworks Inspired by Methodology

Multilevel Modeling

Person-Centered Theorizing

Summary and Concluding Comments

Suggested Readings

Key Terms


IV. Concluding Issues

12. Reading and Writing about Theories

Reading about Theories in Outlets Emphasizing Theory Tests and Confirmatory Approaches to Science

The Introduction Section

The Method Section

The Results Section

The Discussion Section

Reading about Theories in Outlets Emphasizing Grounded/Emergent Theory

Writing about Theories

How You Say It Can Be as Important as What You Say

Briefer Is Better, But Don't Be Too Brief

Prepare an Outline

Provide a Road Map

Provide a Succinct Review of the Current Knowledge

Discuss the Implications and Importance of Your Theory

Keep Your Target Audience in Mind

Using Figures

Cite Sources for Your Ideas, Text, and Related Items

Spelling, Grammar, Typos, and Punctuation

Grant Proposals, Technical Reports, and Presentations

Summary and Concluding Comments

Suggested Readings

Key Terms


APPENDIX 12A. Inferring Theoretical Relationships from the Choice of Statistical Tests

13. Epilogue

Competing Theories

Post Hoc Theorizing

Influential Science

Careers and Creative Theorizing in Science

Scientific Paradigms

A Program of Self Study

Concluding Comments

Suggested Readings

Key Terms


About the Authors

James Jaccard is Professor of Psychology and Director of the Institute for Child Health and Development at Florida International University in Miami. Previously, he was Distinguished Professor of Psychology for 20 years at the State University of New York, Albany. Dr. Jaccard has authored or edited 11 books and over 200 articles in peer-reviewed scientific journals. He has served on numerous boards and panels for the Institute of Medicine of the National Academies and the National Institutes of Health and is a Fellow of the American Psychological Association. His research focuses broadly on attitudes, cognitions, and emotions as they affect decision making, especially in applied settings. This includes research on adolescent decision making, health-related decisions, and a critical analysis of the effects of unconscious influences on adult decision making.

Jacob Jacoby, until his death in 2018, was Merchants Council Professor of Consumer Behavior at New York University’s Stern School of Business. He authored or edited numerous books and over 160 articles in peer-reviewed social science and law journals. Dr. Jacoby was a Fellow of the American Psychological Association and a Fellow and past president of the Association for Consumer Research. His research on the factors that affect consumer decision making and behavior has been honored by awards from the American Psychological Association, the American Marketing Association, the American Academy of Advertising, the Association for Consumer Research, and the Society for Consumer Psychology. He conducted research or consulted for dozens of Fortune 500 companies and other organizations. He also worked for federal agencies (including the U.S. Senate, Federal Trade Commission, and Food and Drug Administration) and testified in more than 100 cases heard in U.S. District Courts.


Graduate students in a range of disciplines, including psychology, education, sociology, health, and management; social scientists pursuing research careers in academic or other settings.

Course Use

Will serve as a primary text in graduate-level courses in theory construction or as a supplemental text in courses on research methodology; theories of a particular discipline; grant writing; or the dissertation.