Research Methodology
Best Practices for Rigorous, Credible, and Impactful Research
1st Edition
Published on 11. June 2024
Book
Paperback/Softback
616 pages
978-1-0718-7194-2 (ISBN)
Description
Research Methodology: Best Practices for Rigorous, Credible, and Impactful Research takes a 360-degree view of understanding and doing research, helping readers become expert researchers, reviewers, and consumers of research. Renowned author, journal editor, and researcher Herman Aguinis distills the vast body of work on methodological best practices into a singular experience. Each of the 16 chapters thoroughly explains a different aspect of methodology step by step, from choosing useful and compelling research topics to reporting results accurately and credibly. Researchers at all career stages will find this text helpful to structure and conduct high-impact empirical research aimed at producing a thesis, dissertation, or journal publication. Research consumers will find instruction on how to evaluate the rigor and credibility of research conducted by others. Instructors will find the book's modular approach refreshing by assigning students the most relevant topics-from checklists of best practices to an in-depth treatment of a methodology. Filled with "how-to's" and "dos and don'ts", figures, hands-on exercises, and "Methods in Practice" boxes that summarize and apply best practices, this book is a must-have for anyone interested in producing or reading research.
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Included with this title:
LMS Cartridge: Import this title's instructor resources into your school's learning management system (LMS) and save time. Don't use an LMS? You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.
Reviews / Votes
This is an interesting, fresh approach, describing the development of research methodologies throughout the years... Much better than my current textbook. -- Verl Anderson This book is easy to read and teach. Students can understand the language and be able to use it with their own research. It is both modern and has history of research within it. Overall, students would benefit in early research to using this book. -- Mindy Myers I can think of no other research methods book I've recently used that devotes this much attention to theory and I think this attention is well-deserved. -- Ewa Golebiowska The discussion or parsimony, falsification, and precision within this book are particularly welcomed and map precisely how I teach these topics. -- Scot Schraufnagel I like that there is a chapter devoted to making connections to theory. This is novel. I have not seen such a chapter in similar texts, and it is important. Often junior scholars ask questions for the sake of simplicity or curiosity but lack the skills to link their inquiries to theory. This chapter is a useful contribution! -- Rachel R. Tambling A high-level but readable textbook presenting research design and methods in an approachable way. The text would be appropriate for graduate level psychology, organizational behavior, or decision sciences courses in research methods. -- Kristina M. Patterson I would describe this book as a long-form publication that provides knowledge on methodological best practices in social and behavioral science disciplines. The writing is explicit and bridges the gap between knowledge and applicability and presents a comprehensive review of the research process from beginning to end. -- Meghan Pfeiffer The text combines research methods and statistics and could work very well for graduate-level programs with combined coursework. -- Michael T. MooreMore details
Language
English
Place of publication
Thousand Oaks
United States
Target group
College/higher education
Dimensions
Height: 254 mm
Width: 203 mm
Thickness: 38 mm
Weight
1137 gr
ISBN-13
978-1-0718-7194-2 (9781071871942)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Herman Aguinis is the Avram Tucker Distinguished Scholar and Professor of Management at The George Washington University School of Business. His interdisciplinary research addresses research methods in the social and behavioral sciences and the acquisition and deployment of talent in organizations. In addition to his about 220 journal articles, 350 keynotes and presentations at professional conferences, and 200 invited presentations, he has published twelve books, including Regression Analysis for Categorical Moderators, Performance Management, and Applied Psychology in Talent Management (with W.F. Cascio). He served as Editor-in-Chief of Organizational Research Methods and received the Academy of Management Research Methods Division Distinguished Career Award for lifetime contributions. He is a three-time recipient of the Academy of Management Research Methods Division Robert McDonald Advancement of Organizational Research Methodology Award, recognizing the best article published in the preceding five years. Also, he received career awards for research contributions from the Society for Industrial and Organizational Psychology and the Society for Human Resource Management, served as President of the Academy of Management, and has been inducted into The PhD Project Hall of Fame. He is a Fellow of the Academy of Management, the American Psychological Association, the Association for Psychological Science, and the Society for Industrial and Organizational Psychology. He serves or has served on the editorial board of 26 journals. The Web of Science Highly Cited Researchers Report has ranked him among the world's 100 most impactful researchers in Economics and Business every year since 2018, and he has about 35,000 LinkedIn and X followers. He is the recipient of the 2024 Academy of Management Diversity, Equity, and Inclusion Division Career Award for Scholarly Contributions. For more information, please visit https://www.hermanaguinis.com
Content
Chapter 1: How to Understand the Current Methodological Landscape
Importance of Research Methods
Research Methods: A Brief Historical Journey
Mapping Quantitative Research Methods
Mapping Qualitative Research Methods: Research Design, Measurement, and Data Analysis
Research on Research Methods: Best in Kind
Research Methods: The Present and the Future
Chapter 2: How to Conduct Ethical Research
Importance of Ethical Research
Research Ethics: Definition and Two Approaches
How to Plan Ethical Research
How to Execute Ethical Research
Special Considerations for Conducting Ethical Research in Field Settings
How to Report Research Results Ethically
How to Enforce Ethical Research
How to Resolve Ethics Complaints
Chapter 3: How to Make Contributions to Theory
Importance of Contributions to Theory
Why Theories Should Be Useful and for Whom
Important Distinctions in Discerning Good Theory
When Is New Theory Needed?
Pruning the Theoretical Landscape
How to Improve Theory Using Theory Elaboration
How to Conduct a Theory Elaboration Study
How to Bridge Levels of Analysis to Improve Theory
Chapter 4: How to Plan Your Research
Importance of Research Planning
How to Address an Important Issue and Conduct Research with a Practical End in Mind
How to Strengthen Causal Inferences
How to Balance the Internal Versus External Validity Tradeoff
How to Choose Control Variables
Illustrations of Best-Practice Recommendations Implementation
Chapter 5: How to Collect Your Sample Using Surveys and Other Means
Importance of Sample Size
Why Large Sample Size Is Not Always the Best Option
How to Make Sure Your Study Participants Are Who You Think They Are
Implementing Best Practices in Merging Your Data with Data from Existing Databases
How to Evaluate the Appropriateness of Your Study's Response Rate When Using Surveys
How to Deal with Publication Bias and the File Drawer Problem
Chapter 6: How to Measure Your Variables
Importance of Measurement
Definition of Measurement and Benefits of Good Measurement
Scales of Measurement
How to Create a New Measure
How to Improve Existing Measures
Chapter 7: How to Design and Conduct Experimental Research
Importance of Experiments
How to Conduct Vignette Experiments
How to Conduct Experiments Online
How to Conduct Experiments Using Virtual Reality
How to Conduct Thought Experiments
Chapter 8: How to Prepare Your Data for Analysis
Importance of Cleaning Up Your Data
How to Handle Missing Data and Data Transformations
How to Handle Outliers
How to Not Clean Up Your Hypotheses by Hypothesizing After Results are Known (HARKing)
Chapter 9: How to Conduct Quantitative Analysis, Part I: Regression-based Approaches
Importance of Regression Analysis
Moderation
Mediation
Analysis of Covariance (ANCOVA)
Using Regression to Understand Nonlinear Effects: The Too-Much-of-A-Good-Thing (TMGT) Effect
Chapter 10: How to Conduct Quantitative Analysis, Part II: Multilevel Modeling
Importance of Multilevel Modeling
Fundamentals of Multilevel Modeling
Visual Representation of Types of Variances Modeled in Multilevel Analysis
Analytic Representation of Sources of Variance Modeled in Multilevel Analysis
The Importance of Statistical Power in Multilevel Modeling
Multilevel Modeling: Step-by-Step Illustration
Why You Need to Examine More than Just the Traditional Intraclass Correlation
Best-practice Recommendations for Conducting and Reporting Multilevel Analysis and Cross-level Interaction Effects
Chapter 11: How to Conduct Quantitative Analysis, Part III: Meta-analysis
Importance of Meta-analysis
Meta-analysis: Choices, Choices, Choices
How to Conduct a State-of-the-science Meta-analysis
Meta-regression
Meta-analytic Structural Equation Modeling
Is There a Need for an Updated Meta-Analysis?
Chapter 12: How to Conduct Quantitative Analysis, Part IV: Advanced Techniques
Importance of Advanced Quantitative Techniques
Market Basket Analysis
Experience Sampling Methodology
Bayesian Analysis
Chapter 13: How to Conduct Qualitative Research
Importance of Qualitative Research
Interviews with Key Informants
Computer-Aided Text Analysis (CATA)
Methodological Literature Reviews
Mixed Methods
How to Improve Transparency and Replicability in Your Qualitative Research
Chapter 14: How to Report Your Results
Importance of How You Report Your Results
How to Report p-values
Why You Should Report Effect Size Estimates
How Your Effect Sizes Compare to Those in Social and Behavioral Research
How to Interpret the Meaning of Effect Sizes
How to Report Statistical Results: The Case of ?2 and ?2
How to Report Your Study's Limitations and Future Research Directions
Chapter 15: How to Improve the Transparency, Reproducibility, and Replicability of Your Research
Importance of Transparency and Replicability of Your Research
How to Improve Transparency about Your Theory
How to Improve Transparency about Your Research Design
How to Improve Transparency about Your Measures
How to Improve Transparency about Your Data Analysis
How to Improve Transparency about Your Results
How to Motivate Authors to Improve Transparency
Chapter 16: How to Enhance the Impact of Your Research
Importance of the Impact of Your Research
Scholarly Impact: Internal and External
On the Use and Misuse of Journal Lists as an Indicator of Scholarly Impact
How to Broaden the Meaning and Measurement of Impact
Actions that University Administrators, Researchers, and Educators Can Take to Enhance Scholarly Impact
How to Create Your Own Personal Impact Development Plan
Enhancing Your Impact: It's a Journey
Importance of Research Methods
Research Methods: A Brief Historical Journey
Mapping Quantitative Research Methods
Mapping Qualitative Research Methods: Research Design, Measurement, and Data Analysis
Research on Research Methods: Best in Kind
Research Methods: The Present and the Future
Chapter 2: How to Conduct Ethical Research
Importance of Ethical Research
Research Ethics: Definition and Two Approaches
How to Plan Ethical Research
How to Execute Ethical Research
Special Considerations for Conducting Ethical Research in Field Settings
How to Report Research Results Ethically
How to Enforce Ethical Research
How to Resolve Ethics Complaints
Chapter 3: How to Make Contributions to Theory
Importance of Contributions to Theory
Why Theories Should Be Useful and for Whom
Important Distinctions in Discerning Good Theory
When Is New Theory Needed?
Pruning the Theoretical Landscape
How to Improve Theory Using Theory Elaboration
How to Conduct a Theory Elaboration Study
How to Bridge Levels of Analysis to Improve Theory
Chapter 4: How to Plan Your Research
Importance of Research Planning
How to Address an Important Issue and Conduct Research with a Practical End in Mind
How to Strengthen Causal Inferences
How to Balance the Internal Versus External Validity Tradeoff
How to Choose Control Variables
Illustrations of Best-Practice Recommendations Implementation
Chapter 5: How to Collect Your Sample Using Surveys and Other Means
Importance of Sample Size
Why Large Sample Size Is Not Always the Best Option
How to Make Sure Your Study Participants Are Who You Think They Are
Implementing Best Practices in Merging Your Data with Data from Existing Databases
How to Evaluate the Appropriateness of Your Study's Response Rate When Using Surveys
How to Deal with Publication Bias and the File Drawer Problem
Chapter 6: How to Measure Your Variables
Importance of Measurement
Definition of Measurement and Benefits of Good Measurement
Scales of Measurement
How to Create a New Measure
How to Improve Existing Measures
Chapter 7: How to Design and Conduct Experimental Research
Importance of Experiments
How to Conduct Vignette Experiments
How to Conduct Experiments Online
How to Conduct Experiments Using Virtual Reality
How to Conduct Thought Experiments
Chapter 8: How to Prepare Your Data for Analysis
Importance of Cleaning Up Your Data
How to Handle Missing Data and Data Transformations
How to Handle Outliers
How to Not Clean Up Your Hypotheses by Hypothesizing After Results are Known (HARKing)
Chapter 9: How to Conduct Quantitative Analysis, Part I: Regression-based Approaches
Importance of Regression Analysis
Moderation
Mediation
Analysis of Covariance (ANCOVA)
Using Regression to Understand Nonlinear Effects: The Too-Much-of-A-Good-Thing (TMGT) Effect
Chapter 10: How to Conduct Quantitative Analysis, Part II: Multilevel Modeling
Importance of Multilevel Modeling
Fundamentals of Multilevel Modeling
Visual Representation of Types of Variances Modeled in Multilevel Analysis
Analytic Representation of Sources of Variance Modeled in Multilevel Analysis
The Importance of Statistical Power in Multilevel Modeling
Multilevel Modeling: Step-by-Step Illustration
Why You Need to Examine More than Just the Traditional Intraclass Correlation
Best-practice Recommendations for Conducting and Reporting Multilevel Analysis and Cross-level Interaction Effects
Chapter 11: How to Conduct Quantitative Analysis, Part III: Meta-analysis
Importance of Meta-analysis
Meta-analysis: Choices, Choices, Choices
How to Conduct a State-of-the-science Meta-analysis
Meta-regression
Meta-analytic Structural Equation Modeling
Is There a Need for an Updated Meta-Analysis?
Chapter 12: How to Conduct Quantitative Analysis, Part IV: Advanced Techniques
Importance of Advanced Quantitative Techniques
Market Basket Analysis
Experience Sampling Methodology
Bayesian Analysis
Chapter 13: How to Conduct Qualitative Research
Importance of Qualitative Research
Interviews with Key Informants
Computer-Aided Text Analysis (CATA)
Methodological Literature Reviews
Mixed Methods
How to Improve Transparency and Replicability in Your Qualitative Research
Chapter 14: How to Report Your Results
Importance of How You Report Your Results
How to Report p-values
Why You Should Report Effect Size Estimates
How Your Effect Sizes Compare to Those in Social and Behavioral Research
How to Interpret the Meaning of Effect Sizes
How to Report Statistical Results: The Case of ?2 and ?2
How to Report Your Study's Limitations and Future Research Directions
Chapter 15: How to Improve the Transparency, Reproducibility, and Replicability of Your Research
Importance of Transparency and Replicability of Your Research
How to Improve Transparency about Your Theory
How to Improve Transparency about Your Research Design
How to Improve Transparency about Your Measures
How to Improve Transparency about Your Data Analysis
How to Improve Transparency about Your Results
How to Motivate Authors to Improve Transparency
Chapter 16: How to Enhance the Impact of Your Research
Importance of the Impact of Your Research
Scholarly Impact: Internal and External
On the Use and Misuse of Journal Lists as an Indicator of Scholarly Impact
How to Broaden the Meaning and Measurement of Impact
Actions that University Administrators, Researchers, and Educators Can Take to Enhance Scholarly Impact
How to Create Your Own Personal Impact Development Plan
Enhancing Your Impact: It's a Journey