Handbook of research methods in social and personality psychology

Cover
Half title
Title
Copyright
Contents
Contributors
Introduction to the Second Edition
Introduction to the First Edition
Chapter one Scratch an Itch with a Brick
	Represent New Perspectives
		Intellectual Puzzles
		Personal Experiences
		Group Identities
		Worldview Defense
		Comment
	Why Run the Study?
		Because This Is Science
		Hitting the Sweet Spot Is Fun
		Solving the Puzzle Is Satisfying
		Being Right Is Fun
		Telling Good Stories Is Entertaining
		Promoting Evidence Is Important
	Sideshows: Pragmatic Reasons for Research
		Publish or Perish
		Collaborate
		Get Rich (or at Least Get Funding)
		Teach
		Serve
		Be Zen
	Conclusion: Why We Do Research
Part one Design and Inference Considerations
	Chapter two Research Design and Issues of Validity
		Research Purpose and Types of Validity
		Internal Validity: The Third-Variable Problem
		Construct Validity: From Construct to Operation and Back Again
			Causes and Confounds
			Construct Validity and Conceptual Replications
			Multiple Operations: Convergent and Discriminant Validity
			Causal Processes and Mediational Analyses
		The Many Faces of External Validity
			Robustness: Can It Be Replicated?
			Ecological Validity: Is It Representative?
			Relevance: Does It Matter?
			Is External Validity Important?
		Optimizing Types of Validity
			Setting: Lab versus Field
			Isolation versus Construct Validity
	Chapter three Research Design
		Focus of This Chapter
		Independent Variables (Factors)
			Fixed or Random Factor?
			Extremity of Levels
			Number of Levels
		Relations among Factors
			Reasons for Using Between-Participants versus Within-Participants Factors
			Reasons for Crossing Factors: I. Testing Theoretically Predicted Interactions (Construct Validity)
			Reasons for Crossing Factors: II. Reducing Error Variance (Statistical Conclusion Validity)
			Reasons for Crossing Factors: III. Establishing Generality of an Effect (External Validity)
			Nonindependence of Observations in Within-Participants Designs
			Counterbalancing and Latin Square Designs
			Nested Factors
		Dependent Variables
			To Pretest or Not to Pretest?
			Selection of Items for Dependent Measure
		Additional Considerations Regarding Design
			Power
			Unequal Ns
			Confounds and Artifacts
			Designs for Studying Mediation
		Concluding Comments
	Chapter four Causal Inference and Generalization in Field Settings
		Rubin’s Causal Model: One Framework for Causal Inference
			Randomization as an Approach to the Fundamental Problem of Causal Inference
			Illustrative Example: Randomization
			Assumptions: Problems and Remedies
			Group Administration of Treatment
		Generalization of Causal Relationships
			Strategies for Generalization
		Quasi-Experimental Designs
			Campbell’s Perspective: A Second Approach to Causal Inference
			Regression Discontinuity Design
			Interrupted Time Series Design
			Nonequivalent Control Group Designs (Observational Studies)
			How Well Do the Alternative Nonrandomized Designs Work?
		Some Final Observations
	Chapter five Field Research Methods
		Introduction
		Laboratory and Field Research
			What Is Field Research?
			Advantages of the Laboratory
			Disadvantages of the Laboratory
			Advantages of the Field
		Field Observational Methods
			Qualitative Methods
			Observation-Based Estimates of Individual or Population Characteristics
			Observation of Situation Characteristics
		Field Experimental Methods
			Randomization and Control in Field Settings
			Encouragement Designs
			Randomized Rollout Designs
			Downstream Field Experimentation
			Hybrid Lab-Field Experiments
			Designs to Address Challenges in the Field
		Quasi-Experimentation in the Field
			Regression Discontinuity
			Interrupted Time Series Analysis
		The Internet as a Site for Experimentation
		Advantages and Disadvantages of Field Experiments
		Practical Issues of Research in Field Settings
		Conclusion
Part two Procedural Possibilities
	Chapter six Using Physiological Indexes in Social Psychological Research
		Background Information
			The Evolution of Social Psychophysiology
			Epistemological Issues
			The Nature of Physiological Indexes of Psychological Constructs
		Basic Physiological Processes
		Control Systems
			Neural Processes
		Cellular Processes
			Endocrine Processes
		Technological Background
			Physiological Response Signals
			Signal Path
			Sensors
		Conditioning
			Recording
		Specific Methodological Concerns
			Threats to Validity
			Design Implications
		Useful Physiological Indexes of Psychological Constructs
			Psychophysiological Indexes of Motivational States: Challenge and Threat
			Rationale
			Validational Research
			Research Examples
			Psychophysiological Indexes of Affective States: Positive and Negative Affect
			Facial EMG Indexes of Positive and Negative Affect
			Research Examples: Prejudice and Discrimination
			Startle Eyeblink Reflex Indexing of Positive and Negative Affect
			Startle Reflex Responses and Social Psychological Research
			Other Physiological Indexes of Psychological Constructs Important to Social Psychologists
		Assessment and Summary
			How Should Interested Social Psychologists Begin the Process of Implementing Psychophysiological Indexes?
			What Sorts of Ideas Are Better or Worse Served by Psychophysiological Indexes?
			What Advantages Accrue to Physiological Indexes?
			Do Physiological Indexes Provide the “Gold Standard” for Psychological Measurement?
			Where Can One Find a Catalog of Valid Physiological Indexes of Psychological Constructs?
	Chapter seven Research Methods in Social and Affective Neuroscience
		Introduction
		Types of Questions That Social Neuroscience Methods can Answer
			Brain Mapping: What Are the Neural Mechanisms of Social-Personality Processes?
			Convergences: How Do Social-Personality Neural Systems Overlap with Other Systems?
			Divergences: Are There Brain Systems Unique to Social-Personality Processes?
		MRI Methods
			Study Design
			Data Acquisition
			Data Cleaning and Preprocessing
			Data Analysis
			Reporting Standards
		Electroencephalogram (EEG) / Event-Related Potentials (ERP) Methods
			Study Design
			Data Collection
			Data Averaging, Cleaning, and Preprocessing
			Analysis of Continuous EEG
		Eight Conceptual Issues in Social Neuroscience (and How to Think Clearly about Them)
			1. Forward and Reverse Inference
			2. Spuriously High Correlations?
			3. Experimental versus Ecological Validity
			4. What Counts as Replication in fMRI and EEG?
			5. Why Is There Greater Fundamental Variability in Social Neuroscience Data?
			6. The Rhetorical Power of Neuroimaging Data
			7. Brain as Predictor: Correlation versus Prediction
			8. Mind Reading?
		Conclusion
		Acknowledgments
	Chapter eight Behavior Genetic Research Methods
		Introduction
		Personality as Nonexperimental Science
		Religiosity and Delinquency in MZ Twins
		Random Effects Models
			Differentiating Genetic and Shared Environmental Confounds
		Structural Equation Models
			Unstandardized ACE Regression
		Modeling Sequence
		Alternative Parameterizations
			Genetically Informed Phenotypic Regression
		Interpretation and Standardization
			Heritability
		Molecular Genetic Approaches
			Linkage Analysis
			Candidate Gene Studies
			Genome-Wide Association Studies
			Genome-Wide Complex Trait Analysis
		Conclusions and Recommendations
	Chapter nine Methods of Small Group Research
		Generic Strategies for Small Group Research
			Field and Archival Research on Groups
			Observational Field Methods
		Nonparticipant Observation
		Participant Observation
		Archival Studies
			Field Experiments
			Experimental Methods
			Systematic Observation of Groups
			Surveys and Interviews
			Computer Simulations
		Methods for Analyzing the Structural Properties of Groups
			Sociometry
			Social Network Analysis
		Innovative Methods and Tools for Group Research
			Audio-Video Hardware and Software
			Computer Technology: Data Collection at Arbitrary Group Tasks
		Groups as a Context/Means for Research and Application
			Group Brainstorming
			Focus Groups
			Quality Circles
			Nominal Group Technique
			Delphi Technique
			Judge Advisor Systems
			Afterword: On the Illusion of Group Effectiveness
		Conclusions
	Chapter ten Inducing and Measuring Emotion and Affect
		Methods for Inducing Affective Changes, Including Emotions
			Films
			Images
			Faces
			Sounds/Voices
			Music
			Imagery and Recall
			Words
			Bodily Movements and Posture
			Physiological Manipulations
			Confederates
			Motivated Performance Tasks
			Virtual Reality
			Real-World Stimuli
		Measuring Evoked States
			Facial Muscle Activity
			Vocal Acoustics
			Observer Ratings
			Behavior
			Autonomic Nervous System Activity
			Central Nervous System Activity
			Endocrine, Immune, and Inflammatory Changes
			Subjective Experiences
		Tips, Tricks, and Secrets for “Best Practices”
	Chapter eleven Complex Dynamical Systems in Social and Personality Psychology
		Dynamical Systems Theory
			What Is a Complex Dynamical System?
			Self-Organization
			Soft-Assembly
			Interaction-Dominant Dynamics
			Nonlinearity
			Chaos
		Dynamical Systems Modeling
			Difference Equations
			Differential Equations
			Attractors
			Order and Control Parameters
			Bifurcations
			Cellular Automata, Agent-Based, and Artificial Neural Network Models
		Dynamical Systems Analysis
			Behavioral Measurement
			Methods of Dynamical Analysis
			Further Reading
		Conclusion
			Acknowledgments
	Chapter twelve Implicit Measures in Social and Personality Psychology
		What Are Implicit Measures?
		An Overview of Basic Paradigms
			Implicit Association Test
			Evaluative Priming Task
			Semantic Priming Tasks
			Affect Misattribution Procedure
			Go/No-Go Association Task
			Extrinsic Affective Simon Task
			Approach-Avoidance Tasks
			Sorting Paired Features Task
			Implicit Relational Assessment Procedure
			Action Interference Paradigm
			How to Choose a Measurement Procedure
		What Can We Learn from Implicit Measures?
			Implicit Measures as a Tool for Predicting Behavior
			Implicit Measures as a Tool for Predicting Biases in Information Processing
			Implicit Measures as a Tool for Understanding the Formation and Change of Mental Representations
		Some Caveats Regarding the Interpretation of Implicit Measures
			Conscious versus Unconscious Representations
			Old versus New Representations
			Dissociations between Explicit and Implicit Measures
			Social Desirability, Faking, and Lie Detection
			Context Effects
			“Automatic” Effects of Experimental Manipulations
			Absolute versus Relative Interpretations
			Multiple Processes Underlying Implicit Measures
		Where Are We Going?
			Mechanisms Underlying Behavior Prediction
			Convergence versus Divergence between Implicit Measures
		Final Remarks
	Chapter thirteen The Mind in the Middle
		The Influence of Internal States on Perceptual Experience
		Individual Differences in Perceptual Experience
		The Roots of Priming Research
			Recent Experience as an Individual Difference
			Priming in Social Psychology
		The Roots of Automaticity Research
			Goal-Dependent Automaticity and Skill Acquisition Research
			Preconscious Processing
		Priming and Automaticity Together
		Priming Research Techniques
		Conceptual Priming
			Supraliminal Priming
			Subliminal Priming
			Supraliminal and Subliminal Priming Compared
			Strength of Priming Manipulations
			Beyond Perception: Goal and Behavior Priming
			What Have We Been Priming All These Years?
		Mindset Priming
			Unwanted Effects of Priming
			Demand Characteristics and Mindset Priming
		Automaticity Research Techniques
			Efficiency
			Unintended Processing Effects
			Some Issues Concerning the Use of Response Latencies as a Dependent Variable
			Uncontrollability
			How Control Attempts Can Produce Uncontrollability
		Conclusions
		Appendix A: Examples of Scrambled Sentence Tests
		Appendix B: Example of Funneled Debriefing Procedure for Supraliminal Priming Task
		Appendix C: Example of a Subliminally Presented Pattern Used as a Forward and Backward Mask
	Chapter fourteen Behavioral Observation and Coding
		Behavioral Observation and Coding
		What Is Behavioral Observation?
		Why Use This Research Method?
		Observational Settings
			Naturalistic Observation
			Quasi-Naturalistic Observation
			Analogue Observation
			Experimental Manipulation
		Behavioral Observation Coding Systems
			Coding Units
			Molar versus Molecular Approach
			Multiple Dimensions
			Example
		Training Observers
		Interrater Agreement
			Which Interrater Agreement Statistic to Use
			Categorical Observations
			Ordinal, Interval, and Ratio Observations
			Interrater Agreement for Sequences
		Reliability across Observations, Contexts, and Time
			How Much Time Is Necessary to Achieve Acceptable Reliability?
		Validity
		Analyzing Behavioral Observation Data
			Sequential Analysis
			Loglinear Approach to Sequential Analysis
			Dimensional Analyses of Behavior Sequences
			Recent Developments in Analyzing Observational Data
		Conclusions and Future Directions
	Chapter fifteen Methods for Studying Everyday Experience in Its Natural Context
		The Conceptual Rationale for Everyday Experience Methods
			Research Aims
			Conceptualizing Everyday Experience
		The Methodological Rationale for Everyday Experience Methods
		Diary Data as Self-Reports
		Types of Everyday Experience Protocols
			Interval-Contingent Recording
			Signal-Contingent Recording
			Event-Contingent Recording
			Comparison of Protocols
		Pragmatic Considerations in Everyday Experience Research
			Designing the Protocol
			Format of Administration
			Designing the Instrument
			Participant Issues
		Does Record-Keeping Alter Experience?
		Data Analytic Strategies and Considerations
			Aggregation and Composites
			The Logic of Multilevel Modeling of Everyday Experience Data
			Complex Multilevel Models
			Analysis of Temporal Patterns
		Integrating Everyday Experience Methods in Programmatic Research
		Concluding Comments
	Chapter sixteen Survey Research
		Study Designs
			Cross-Sectional Surveys
			Repeated Cross-Sectional Surveys
			Panel Surveys
			Combined Use of Cross-Sectional and Panel Surveys
			Experiments within Surveys
			Implicit Measurement
		Sampling
			Probability Sampling
			Threats to Sample Representativeness
			Nonprobability Sampling
		Questionnaire Design and Measurement Error
			Open vs. Closed Questions
			Rating versus Ranking
			Rating Scale Formats
			The Order of Response Alternatives
			No-Opinion Filters and Attitude Strength
			Question Wording
			Question Order
			Questions to Avoid
		Pretesting
			Pretesting Methods for Interviewer-Administered Questionnaires
			Self-Administered Questionnaire Pretesting
		Data Collection
			Mode
			Choosing a Mode
			Interviewing
		Total Survey Error
		Conclusions
	Chapter seventeen Conducting Research on the Internet
		Conceptual Issues
			Why Collect Data over the Internet?
			Challenges in Internet Research
		How to Create Studies on the Internet
			Hosting the Study Webpages
			Creating the Study Webpages
			Questions You Should Ask When Selecting an Internet-Hosting Service
		Specific Internet Study Designs
			Implementing Experiments Online
			Implementing Indirect Measures and Tasks Online
			Implementing Longitudinal and Experience Sampling Studies
		Study Design Considerations
			Ordering of Questions
			Number of Questions per Page
			Formatting for Presentation across Diverse Platforms
			Professional Presentation
			Making Questions Mandatory
			Measuring Attention
			Engaging Attention
			Study Length
			Managing Dropout
			Pretesting
			Data Cleaning
		Recruitment and Sampling Strategies
			Online Forums and Websites
			Websites Listing Online Studies
			Online Advertising
			Email Distribution Lists and Listservs
			Enhancing Response Rates from Email Invitations
			Probability-Based Internet Panels
			Crowdsourcing
			Snowball Recruitment
			Monetary Recruitment Incentives
			Feedback as a Recruitment Incentive
		Ethical Issues
			Informed Consent
			Public vs. Private Behavior
			Maintaining Data Security
			IP Addresses and Anonymity
			Greater than Minimal Risk Studies
			Deception and Debriefing
		Concluding Comments: The Future of Internet-Based Research
Part three Data Analytic Strategies
	Chapter eighteen Measurement
		Some General Considerations in Measurement
			Defining Measurement as Building and Evaluating Models
			Psychometric and Representational Approaches to Measurement
			Overview
		Reliability and Generalizability
			Classical Test Theory
			Specific Types of Reliability Evidence
			Coefficient Alpha: Ubiquitous but Not a Panacea
			Correcting for Attenuation
			Reporting Basic Psychometric Data
			Beyond Classical Test Theory: Generalizability Theory
			Item Response Theory
		Construct Validation
			Traditional Definitions of Validity
			An Integrated Conception of Construct Validity
			Types of Evidence for Construct Validity
			External Validation: Convergent and Discriminant Aspects
		Model Testing in Construct Validation and Scale Construction
			Measurement Models in SEM: Convergent Validity, Discriminant Validity, and Random Error
			Issues in Questionnaire Construction
		Conclusions and Recommendations
	Chapter nineteen Exploring Causal and Noncausal Hypotheses in Nonexperimental Data
		Why Conduct Nonexperimental Studies?
		“Experimental” Versus “Nonexperimental” Statistical Methods
		Analyses Addressing Noncausal Hypotheses
			Exploratory Factor Analysis
			Confirmatory Factor Analysis
			Statistical Issues in CFA
			Multidimensional Scaling
			Summary and Comparison of Noncausal Methods
		Analyses Involving Causal Hypotheses
			Types of Causal Hypotheses
			Conditions for Inferring Causality
			Regression
			Multilevel Models
			Structural Equation Modeling
			Statistical Issues in SEM
			Types of Hypotheses
			Design Issues in the Use of SEM
			Summary of Methods Addressing Causal Hypotheses
		Conclusions
	Chapter twenty Advanced Psychometrics
		Confirmatory Factor Analysis
			CFA Model
			Data Requirements for CFA
			Implementing CFA
			Two Empirical Examples
			Factorial Invariance in CFA Models
		Item Response Theory
			Dichotomous Item Response Models
			Polytomous Item Response Models
			Item and Test Information
			Data Requirements
			Empirical Example
			Examining Measurement Invariance with IRT Models
		Summary Comments
	Chapter twenty-one Multilevel and Longitudinal Modeling
		Levels
		Aggregation and Disaggregation
		Basics of Multilevel Modeling and Structural Equation Modeling
		Multilevel Modeling
		Intraclass Correlation Coefficient
		Structural Equation Modeling (SEM)
		Common Research Designs with Nested Data
		Cross-Sectional Designs
		Longitudinal Designs
		Panel Designs
		Latent Growth Curves
		Multilevel SEM
		Conclusion
	Chapter twenty-two The Design and Analysis of Data from Dyads and Groups
		Terminology and Definitions
			Independence of Observations
			Types of Variables
			Distinguishability
		Multilevel Modeling
			MLM and Group Data
			MLM and Dyadic Data
			Negative Nonindependence
		Dyadic Data and the Actor-Partner Interdependence Model
			Patterns
			Example
			Mediation and Moderation
		Group Studies
			Extension of the APIM to Groups
			Dyadic Outcomes: The Social Relations Model
			Intergroup Research
		One-With-Many Design
		Conclusion
	Chapter twenty-three Nasty Data
		Source of Problems
			Why Worry?
		Methods for Detecting Nasty and Ill-Mannered Data
			Single Groups
			Two Groups
			Multiple Groups
			Simple Regression
			Multiple Regression
		Remedies
			Nonparametric Statistics
			Transformations
			Outliers
		Example
		Conclusion
	Chapter twenty-four Missing Data Analysis
		Missing Data Mechanisms
			Missing Completely at Random (MCAR)
			Missing at Random (MAR)
			Not Missing at Random (NMAR)
			Summary
		Planned Missing Data Designs
			Two-Method Measurement Design
			Three-Form Design
			Planned Missing Data Designs for Repeated Measures
		Traditional Missing Data Handling Methods
			Deletion Methods
			Mean Imputation and Averaging the Available Items
			Regression Imputation
			Stochastic Regression Imputation
		Multiple Imputation
			Imputation Phase
			Analysis Phase
			Pooling Phase
		Maximum Likelihood Estimation
			How Including the Incomplete Cases Improves Accuracy
			Auxiliary Variables
		Comparing Multiple Imputation and Maximum Likelihood Estimation
			Practical Considerations
			Choosing Multiple Imputation
		NMAR-Based Analyses
		Summary
	Chapter twenty-five Mediation and Moderation
		Defining Mediation and Moderation
		Mediation
			Basic Analytic Model
			Assumptions
			Estimating and Testing Indirect Effects
			Observed versus Latent Variable Models
			Multilevel mediation
			From Measured to Manipulated Mediators
		Moderation
			Definitions and Basic Models
			Interpretation and Presentation
			Difficulties of Detecting Interactions
			Multilevel Interactive Models
		Moderated Mediation and Mediated Moderation
		Conclusion
	Chapter twenty-six Meta-Analysis of Research in Social and Personality Psychology
		Procedures for Meta-Analysis
			An Overview of the Process of Quantitative Synthesis
			Conceptual Analysis of the Literature
			Setting Boundaries for the Sample of Studies
			Locating Relevant Studies
			Estimating Effect Sizes in Individual Studies
			Using Arithmetic Means to Gauge a Quantity’s Magnitude
			Analyzing the Meta-Analytic Database
		Conducting and Evaluating Meta-Analyses
		Additional Resources on Research Synthesis
		The Future of Meta-Analysis in Social and Personality Psychology
		Appendix A: Estimating  Effect Sizes in Individual Studies
			Effect Sizes from Means and Standard Deviations
			Effect Sizes from t- and F-values
			Effect Sizes from r-values
			Effect Sizes from Chi-square Values
			Effect Sizes from Proportions Meeting a Criterion
			Effect Sizes from Probabilities Associated with Inferential Statistics
Author Index
Subject Index