Advanced Research Methods For The Social And Behavioral Sciences 1st edition by John Edlund 1108572934 9781108572934

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ISBN-10 :  1108572934 

ISBN-13 :  9781108572934

Author:  John E. Edlund 

Written by an interdisciplinary team of global experts covering diverse research methods – including research design, research tools, and statistical techniques – this volume focuses on advanced research methods for anyone working in the social and behavioral sciences. The information needed to perform research in the laboratory, the field, or online is mapped out to provide specific applications and tools in applying each method. The issues surrounding reliability, validity, and obtaining consent are explained alongside detailed descriptions of the impact of pre-knowledge on participant behavior, the ways that researchers unintentionally influence participants, and tips on administering suspicion probes and debriefings. The book then lays out bio-physiological measures, eye-tracking methods and technologies, the construction of questionnaires, and reaction-time methodologies without assuming too much prior knowledge. The basics of Bayesian analysis, item response analysis, social network analysis, and meta-analysis are also summarised as the editors combine innovative methods and statistics to showcase how to perform quality research.

Advanced Research Methods For The Social And Behavioral Sciences 1st table of contents: 

1 A Brief Orientation to Research Methods and Statistics for the Social and Behavioral Sciences
1.1 What Is Good Science?
1.2 Research Methods
1.2.1 Quantitative and Qualitative Research
1.2.2 Theories and Hypotheses
1.2.3 Operationalization and Constructs
1.2.4 Variables
1.2.5 Reliability and Validity
1.3 Data
1.4 Statistics
1.4.1 Measures of Central Tendency
1.4.2 Measures of Distribution
1.5 Statistical Analyses
1.5.1 Moderation and Mediation
1.5.2 Correlation
1.5.3 T-Test
1.5.4 ANOVA
1.5.5 Regression
1.5.6 Factor Analysis
1.5.7 Chi-Square
1.6 Conclusion
Key Takeaways
Suggested Readings
References
Part One: Performing Good Research
2 Reliability and Validity of Measurement in the Social and Behavioral Sciences
2.1 The Pursuit of Evidence for Reliability
2.1.1 The Test-Retest Method
2.1.2 Use of Parallel Forms to Assess Reliability
2.1.3 Assessing Reliability via Internal Consistency
2.1.4 Reliability in Measures Made by Different Researchers
2.1.5 Why Report Evidence about Reliability?
2.2 The Pursuit of Evidence for Construct Validity
2.2.1 Construct Validity and Convergence with Other Measures
2.2.2 Construct Validity and Divergence with Other Measures
2.2.3 From the Trees to the Forest: Using the Various Measures of Validity
2.2.4 Considerations in the Documentation and Use of Validity
2.3 Coda
Key Takeaways
Ideas for Future Research
Suggested Readings
References
3 Performing Research in the Laboratory
3.1 What Makes a Laboratory?
3.2 Advantages and Disadvantages
3.2.1 Advantages
3.2.2 Disadvantages
3.3 Types of Lab Research
3.3.1 Experiment
3.3.2 Quasi-Experiment
3.3.3 Surveys
3.4 Issues to Consider
3.4.1 Participants
Recruitment.
Biases.
Debriefing.
3.4.2 Research Assistants
Recruitment.
Training.
3.4.3 Deception
Tradeoffs.
Types of Deception.
Effectively Using Deception.
3.4.4 Applying Results to the Real World
Does Lab Research Generalize?
Tips for Increasing Generalizability.
3.5 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
4 Field Research
4.1 Getting Started
4.2 Locating the Self in Fieldwork
4.2.1 Fitting In: On Insiders and Outsiders
4.3 Getting In
4.4 Writing Fieldnotes
4.5 A Note on Ethics
4.6 Developing an Analysis
4.7 Getting Out
4.8 Looking Ahead
4.9 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
5 Using the Internet for Research
5.1 Overview of Present Chapter
5.2 Conducting Internet Research
5.2.1 Why Do Social Scientists Conduct Internet Research?
5.2.2 What Topics Do Social Scientists Study on the Internet?
5.3 Crowdsourced Data Collection
5.3.1 Amazon’s Mechanical Turk (MTurk)
5.3.2 Snowball Sampling
5.4 Big Data: Collecting Data Directly from People’s Internet Activity
5.5 Linguistic Analysis of People’s Posts
5.6 Ethical Considerations
5.6.1 Participant Anonymity, Confidentiality, and Consent
5.6.2 Privacy Concerns
5.6.3 Non-Naïveté and Honesty in Participants
5.6.4 Fair Compensation
5.7 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
Part Two: Understanding Issues Present Throughout the Research Process
6 Issues in Informed Consent
6.1 Concerns About and Strategies to Improve Informed Consent
6.1.1 Intelligence
Assessment.
Surrogates and Legally Authorized Representatives.
6.1.2 Knowingness
Comprehending and Recalling Consent and Study Information.
Therapeutic Misconception.
Strategies for Improving Knowingness.
Modifying the Structure of Consent Documents.
Modifying the Consent Process.
Enhancing Motivation.
Consent Quizzes.
Multimedia Consent Approaches.
Obtaining Informed Consent Remotely.
6.1.3 Voluntariness
Strategies to Help Ensure Voluntariness.
Assessment.
Research Intermediaries.
6.2 Cultural Context
6.3 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
7 Participant Preknowledge and Attitudes in Research
7.1 The Role of Measurement in the Research Process
7.1.1 Participant Preknowledge
7.1.2 Attitudes Beyond Crosstalk
7.2 Controlling for the Effects of Preknowledge and Attitudes
7.3 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
8 Experimenter Effects
8.1 Noninteractional Experimenter Effects
8.2 Minimizing Potential Noninteractional Experimenter Effects
8.3 Interactional Experimenter Effects
8.4 Minimizing Interactional Experimenter Effects in Research
8.5 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
9 Suspicion Probes and Debriefing in the Social and Behavioral Sciences
9.1 Deception in Research
9.2 Participant Suspicion
9.3 Debriefing and Probing for Suspicion
9.3.1 Debriefing
9.3.2 Probing for Suspicion
9.3.3 Adequacy of Postexperimental Inquiries
9.3.4 Handling Data Collected from Postexperimental Inquiries
9.4 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
Part Three: The Social and Behavioral Scientist’s Toolkit
10 Physiological Measures
10.1 Basic Principles
10.2 Autonomic Measures
10.2.1 Electrodermal activity (EDA)
10.2.2 Cardiovascular System
10.3 EMG and Startle Eyeblink
10.3.1 Facial Expressions and EMG
10.3.2 Startle Eyeblink
10.4 Hormones
10.5 EEG and ERPs
10.5.1 EEG
10.5.2 Event-Related Potentials (ERPs)
10.6 Functional MRI and PET
10.7 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
11 Eyetracking Research
11.1 Background
11.2 Remote Eyetrackers
11.3 Tower Eyetrackers
11.4 Headband-Mounted Eyetrackers
11.5 Wearable Eyetrackers
11.6 Head-Mounted Display (HMD) Eyetrackers
11.7 Selecting an Eyetracker
11.8 Data Quality
11.9 Sample Applications
11.10 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
12 Questionnaire Design
12.1 Considerations Prior to Questionnaire Development
12.1.1 Distribution Method
Self-Administered Questionnaires.
Investigator-Administered Questionnaires.
Design Considerations.
12.1.2 Exploring Extant Measures
12.1.3 Testing the Instrument
12.1.4 Self-Report Limitations
12.2 Questionnaire Design
12.2.1 Instructions
12.2.2 Inclusion of Demographics
12.3 Question Considerations
12.3.1 Mutually Exclusive Options
12.3.2 Exhaustive Options
12.3.3 Reverse Coded Questions
12.3.4 Types of Questionnaire Scales
Likert-Type.
Guttman.
Semantic Differential.
Open-Ended Questions.
12.4 Limitations to Questionnaire Design
12.5 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
13 Reaction Time Measures in the Social and Behavioral Sciences: Speed Matters
13.1 A Brief History of Reaktionszeit
13.1.1 On the ”Incompetence” of Astronomers’ Assistants
13.1.2 On the ”Nerve” of Nineteenth-Century Physiologists
13.1.3 Wundt Brings RT to Social and Behavioral Science
13.2 The State of Reaction Time Research Today
13.2.1 Stimulus Intensity and Complexity
13.2.2 Arousal
13.2.3 Focus of Attention Effects
13.2.4 Practice Effects
13.3 Commonly Employed Reaction Time Measures in the Social and Behavioral Sciences
13.3.1 The Stroop Color and Word Test
13.3.2 The Eriksen Flanker Task
13.3.3 Evaluative Priming
13.3.4 The Implicit Association Test
13.3.5 The Go/No-Go Association Task
13.4 Instruments for the Reaction Time Researcher’s Toolbox
13.4.1 DirectRT
13.4.2 E-Prime
13.4.3 SuperLab
13.4.4 Online and Open-Source Tools
13.5 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
Part Four: Emerging Issues in Social and Behavioral Science Research
14 Replications and the Social and Behavioral Sciences
14.1 Defining Replication
14.1.1 Types of Replications
14.1.2 Scales of Replications
14.2 How Replications Build Knowledge
14.3 Past Replication Attempts
14.4 How to Conduct Replications
14.4.1 What Is the Purpose of the Replication?
14.4.2 Operationalizing the Replication
14.4.3 Contacting Original Authors
14.4.4 Choosing a Sample Size
14.4.5 Pre-registering Replications
14.4.6 Reporting Replications
14.5 Interpreting Replication Results
14.6 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
15 Research Ethics for the Social and Behavioral Sciences
15.1 The Ethical Principles of Research
15.1.1 Honesty
15.1.2 Objectivity
15.1.3 Accountability
15.1.4 Authenticity
Fabrication.
Falsification.
Plagiarism.
15.1.5 Compliance
15.2 Turning to Context
15.2.1 Universities, Research Centers, and Government Agencies
15.2.2 The Scientific Community
Responsible Teamwork.
Responsible Authorship.
Responsible Peer Reviewing and Editing.
Responsible Mentoring.
Responsible Data Management.
15.2.3 Dealing with Human Subjects
Avoid Any Kind of Harm.
Valid Consent.
Respecting Privacy.
15.3 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
16 Interdisciplinary Research
16.1 What Does Interdisciplinary Research Mean?
16.2 How Is an Effective Team Assembled and Managed?
16.3 Strong Leadership
16.4 Selected Team Members
16.5 Optimizing Attributes of Interdisciplinary Collaboration: Strong Working Relationships
16.6 Communication
16.7 Challenges in Working across Disciplines
16.8 Promoting IDR
16.9 Funding Opportunities
16.10 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
17 Cross-Cultural Research
17.1 What Is Cross-Cultural Research?
17.2 Specific Topics of Cross-Cultural Studies
17.2.1 Taxonomy of Equivalence and Bias
Equivalence.
Bias.
17.3 Test Adaptations
17.4 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
Part Five: New Statistical Trends in the Social and Behavioral Sciences
18 A Gentle Introduction to Bayesian Statistics
18.1 Overview
18.2 Data and Research Question
18.2.1 Data
18.2.2 Research Question and Hypothesis
18.2.3 Parameters to Be Estimated
18.3 Frequentist Options
18.4 Bayesian Options
18.4.1 Parameter Estimation with Diffuse Priors
18.4.2 Reporting Non-Significant Findings
18.4.3 Parameter Estimation with Informative Priors
18.4.4 Sensitivity Analysis
18.5 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
19 Development and Applications of Item Response Theory
19.1 The Rasch Model and Basic Principles of IRT
19.2 Additional Unidimensional IRT Models
19.2.1 The Two Parameter Logistic Model
19.2.2 The Three Parameter Logistic Model
19.3 Unidimensional Models for Polytomous Responses
19.4 Estimating Item and Person Parameters
19.4.1 Maximum Likelihood (ML)
19.4.2 Marginal Maximum Likelihood (MML)
19.4.3 Maximum A Posteriori (MAP) and Expected A Posteriori (EAP)
19.5 Assumptions of IRT
19.6 Model Fit
19.6.1 Overall Model Fit
19.6.2 Item Fit
19.7 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
20 Social Network Analysis
20.1 What Is Social Network Analysis?
20.1.1 Foundations and Key Ideas
20.2 Understanding, Collecting, and Visualizing Network Data
20.2.1 Terminology
20.2.2 Network Data
20.2.3 Sources of Network Data
20.2.4 Data Collection
Ego Network Design.
Complete Network Design.
Network Boundaries and Sampling.
Network Survey Questions.
Ethical Considerations.
20.2.5 Data Organization
20.2.6 Data Visualization
20.3 Describing Network Data
20.3.1 Node Level
20.3.2 Dyad/Tie Level
20.3.3 Triad Level: Cohesion and Embedding of Ties
20.3.4 Subgroup and Full Network
20.4 Explaining Network Structure
20.4.1 Dependence of Observations
20.4.2 Controlling for Dependence of Observations
20.4.3 Specifying Dependencies
Models for Cross-Sectional Data.
Models for Longitudinal Data.
ERGM Derivatives.
Stochastic Actor Oriented Models.
Models for Continuous Data.
20.5 Conclusion
Key Takeaways
Ideas for Future Research
Suggested Readings
References
21 Meta-Analysis: An Introduction
21.1 Search, Selection, and Extraction
21.1.1 Published Works
21.1.2 Unpublished Works
21.1.3 Coding
21.2 Meta-Analytic Approaches
21.2.1 Vote-Counting
21.2.2 Effect Size Heterogeneity
21.2.3 Fixed- Versus Random-Effects Meta-Analysis
21.2.4 Correcting for Bias and Artifacts: Raw Versus Adjusted Effect Sizes
21.2.5 Univariate, Bivariate, and Multivariate Meta-Analysis
21.2.6 Structural Equation Modeling Approach
21.3 Meta-Analysis Programs
21.4 Outliers, Publication Bias, Decline Effects
21.4.1 Outliers
21.4.2 Publication Bias
Fail-Safe N.
Funnel Plot.
Trim and Fill.
Egger’s Test.
PET-PEESE.
Cumulative Meta-Analysis.
Summary.
21.4.3 Decline Effects
21.5 Example: Convergent Validity in Measures of Self-Esteem Instability
21.5.1 Raw Correlations
Detecting Outliers and Publication Bias.
Moderation.
21.5.2 Corrected Correlations
21.5.3 Additional Examples
21.6 Meta-Analysis: Limitations and Alternatives
21.6.1 Limitations
21.6.2 Overview of Alternatives
21.7 Conclusion

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