Research Design and Methods: A Process Approach

✍ Scribed by Kenneth S. Bordens, Bruce B. Abbott

• Publisher: McGraw Hill
• Year: 2022
• Tongue: English
• Leaves: 657
• Edition: 11
• Category: Library

✦ Table of Contents

Cover
Research Design and Methods: A Process Approach
Dedication
Contents
Preface
Acknowledgments
Chapter 1: Explaining Behavior
Practicing Science
What Scientists Do
Science as a Way of Thinking
Basic and Applied Research
Learning About Research: Why Should You Care?
Exploring the Causes Of Behavior
Explaining Behavior
Science, Protoscience, Nonscience, and Pseudoscience
Scientific Explanations
Commonsense Explanations Versus Scientific Explanations
Belief-Based Explanations Versus Scientific Explanations
When Scientific Explanations Fail
Failures Due to Faulty Inference
Pseudoexplanations
The Emergence of New, Conflicting Information
Other Methods of Inquiry
The Method of Authority
The Rational Method
Steps in the Research Process
Developing a Research Idea and Hypothesis
Choosing a Research Design
Choosing Subjects
Deciding on What to Observe and Appropriate Measures
Conducting Your Study
Analyzing Your Results
Reporting Your Results
Starting the Whole Process Over Again
Summary
Key Terms
References
Chapter 2: Developing and Evaluating Theories of Behavior
What Is a Theory?
Theory Versus Hypothesis
Theory Versus Law
Theory Versus Model
Mechanistic Explanations Versus Functional Explanations
Classifying Theories
Is the Theory Quantitative or Qualitative?
At What Level of Description Does the Theory Operate?
What Is the Theory’s Domain?
Roles of Theory in Science
Understanding
Prediction
Organizing and Interpreting Research Results
Generating Research
Characteristics of a Good Theory
Ability to Account for Data
Explanatory Relevance
Testability
Prediction of Novel Events
Parsimony
Strategies for Testing Theories
Following a Confirmational Strategy
Following a Disconfirmational Strategy
Using Confirmational and Disconfirmational Strategies Together
Using Strong Inference
Theory-Driven Versus Data-Driven Research
Summary
Key Terms
References
Chapter 3: Understanding Ethical Issues in the Research Process
Ethical Research Practice With Human Participants
John Watson and Little Albert
Is It Fear or Is It Anger?
Putting Ethical Considerations in Context
The Evolution of Ethical Principles for Research with Human Participants
The Nuremberg Code
The Declaration of Helsinki
The Belmont Report
APA Ethical Guidelines
Government Regulations
Internet Research and Ethical Research Practice
Ethical Guidelines, Your Research, and the Institutional Review Board
Ethical Considerations When Using Animal Subjects
The Institutional Animal Care and Use Committee
Cost–Benefit Assessment: Should the Research Be Done?
Treating Science Ethically
What Constitutes Misconduct in Research?
The Prevalence of Research Misconduct
Explanations for Research Misconduct
Detecting and Dealing with Research Misconduct
Summary
Key Terms
References
Chapter 4: Getting Ideas for Research
Sources of Research Ideas
Experience
Theory
Applied Issues
Developing Good Research Questions
Asking Answerable Questions
Asking Important Questions
Developing Research Ideas: Reviewing the Literature
Reasons for Reviewing the Scientific Literature
Sources of Research Information
Searching the Scientific Literature
Research Tools
Conducting an Electronic Database Search
A Note of Caution When Searching an Electronic Database
The Basic Strategy for Conducting a Thorough Search
Searching for Books and Other Library Materials
Reading a Research Report
Reading the Literature Critically
Factors Affecting the Quality of a Source of Research Information
Publication Practices
Statistical Significance
Consistency with Previous Knowledge
Significance of the Contribution
Editorial Policy
Peer Review
Values Reflected in Research
Developing Hypotheses
Summary
Key Terms
References
Chapter 5: Choosing a Research Design
Functions of a Research Design
Causal Versus Correlational Relationships
Correlational Research
An Example of Correlational Research: Bullying and Adolescent Suicide
Causation and the Correlational Approach
Why Use Correlational Research?
Experimental Research
Characteristics of Experimental Research
An Example of Experimental Research: Violent Video Games and Aggressive Emotion
Strengths and Limitations of the Experimental Approach
Experiments Versus Demonstrations
Internal and External Validity
Internal Validity
External Validity
Internal Versus External Validity
Research Settings
The Laboratory Setting
The Field Setting
A Look Ahead
Summary
Key Terms
References
Chapter 6: Making Systematic Observations
Deciding What to Observe
Choosing Specific Variables for Your Study
Research Tradition
Theory
Availability of New Techniques
Availability of Equipment
Choosing Your Measures
Physical Versus Psychological Measures
Reliability of a Measure
Accuracy of a Measure
Validity of a Measure
Acceptance as an Established Measure
Scale of Measurement
Variables and Scales of Measurement
Choosing a Scale of Measurement
Adequacy of a Dependent Measure
Tailoring Your Measures to Your Research Participants
Types of Dependent Variables and How to Use Them
The Reactive Nature of Psychological Measurement
Reactivity in Research with Human Participants
Reactivity in Research with Animal Subjects
Automating Your Experiments
Detecting and Correcting Problems
Conducting a Pilot Study
Adding Manipulation Checks
Summary
Key Terms
References
Chapter 7: Choosing and Using Research Subjects
General Considerations
Populations and Samples
Sampling and Generalization
Nonrandom Sampling
Is Random Sampling Always Necessary?
Acquiring Human Participants for Research
The Research Setting
The Needs of Your Research
Institutional Policies and Ethical Guidelines
Voluntary Participation and Validity
Factors That Affect the Decision to Volunteer
Volunteerism and Internal Validity
Volunteerism and External Validity
Remedies for Volunteerism
Research Using Deception
Research Deception in Context
Types of Research Deception
Problems Involved in Using Deception
Solutions to the Problem of Deception
Considerations When Using Animals as Subjects in Research
Contributions of Research Using Animal Subjects
Choosing Which Animal to Use
Why Use Animals?
How to Acquire Animals for Research
Generality of Animal Research Data
The Animal Rights Movement
Animal Research Issues
Alternatives to Animals in Research: In Vitro Methods and Computer Simulation
Summary
Key Terms
References
Chapter 8: Doing Nonexperimental Research
Making and Assessing Direct Observations
Developing Behavioral Categories
Quantifying Behavior in an Observational Study
Recording Single Events or Behavior Sequences
Making Your Observations Live or from Recordings
Coding the Behaviors
Coping with Complexity: Sampling Strategies
Establishing the Accuracy and Reliability of Your Observations
Sources of Bias in Observational Research
Quantitative and Qualitative Approaches to Data Collection
Nonexperimental Research Designs
Naturalistic Observation
Ethnography
Sociometry
The Case History
Archival Research
Content Analysis
Meta-Analysis: A Tool for Comparing Results Across Studies
Step 1: Identifying Relevant Variables
Step 2: Locating Relevant Research to Review
Step 3: Conducting the Meta-Analysis
Drawbacks to Meta-Analysis
Summary
Key Terms
References
Chapter 9: Doing Survey Research
Survey Research
Designing Your Questionnaire
Writing Questionnaire Items
Assembling Your Questionnaire
Administering Your Questionnaire
Mail Surveys
Internet Surveys
Telephone Surveys
Group-Administered Surveys
Face-to-Face Interviews
Mixed-Mode Surveys
A Final Note on Survey Techniques
Assessing the Reliability of Your Questionnaire
Assessing Reliability by Repeated Administration
Assessing Reliability with a Single Administration
Increasing Reliability
Assessing the Validity of Your Questionnaire
Acquiring a Sample for Your Survey
Representativeness
Sampling Techniques
Random and Nonrandom Sampling Revisited
Sample Size
Summary
Key Terms
References
Chapter 10: Using Between-Subjects and Within-Subjects Experimental Designs
Types of Experimental Design
The Problem of Error Variance In Between-Subjects and Within-Subjects Designs
Sources of Error Variance
Handling Error Variance
Between-Subjects Designs
The Single-Factor Randomized-Groups Design
Matched-Groups Designs
Within-Subjects Designs
An Example of a Within-Subjects Design: Does Caffeine Keep Us Going?
Advantages and Disadvantages of the Within-Subjects Design
Sources of Carryover
Dealing with Carryover Effects
When to Use a Within-Subjects Design
Within-Subjects Versus Matched-Groups Designs
Types of Within-Subjects Designs
Factorial Designs: Designs with Two or More Independent Variables
An Example of a Factorial Design: Smoker’s Recall of Fear-Appeal Imagery
Main Effects and Interactions
Factorial Within-Subjects Designs
Higher-Order Factorial Designs
Other Group-Based Designs
Designs With Two or More Dependent Variables
Confounding and Experimental Design
Summary
Key Terms
References
Chapter 11: Using Specialized Research Designs
Combining Between-Subjects and Within-Subjects Designs
The Mixed Design
The Nested Design
Combining Experimental and Correlational Designs
Including a Covariate in Your Experimental Design
Including Quasi-Independent Variables in an Experiment
An Example of a Combined Design: Is Coffee a Physical or Psychological Stimulant?
Quasi-Experimental Designs
Time Series Designs
Equivalent Time Samples Design
Advantages and Disadvantages of Quasi Experiments
Nonequivalent Control Group Design
Pretest–Posttest Designs
Problems with the Pretest–Posttest Design
The Solomon Four-Group Design
Eliminating the Pretest
Developmental Designs
The Cross-Sectional Design
The Longitudinal Design
The Cohort-Sequential Design
Summary
Key Terms
References
Chapter 12: Using Single-Subject Designs
A Little History
Baseline, Dynamic, and Discrete Trials Designs
Baseline Designs
An Example Baseline Experiment: Do Rats Prefer Signaled or Unsignaled Shocks?
Issues Surrounding the Use of Baseline Designs
Dealing with Uncontrolled Variability
Determining the Generality of Findings
Dealing with Problem Baselines
Types of Single-Subject Baseline Design
Dynamic Designs
Discrete Trials Designs
Characteristics of the Discrete Trials Design
Analysis of Data from Discrete Trials Designs
Inferential Statistics and Single-Subject Designs
Advantages and Disadvantages of the Single-Subject Approach
Summary
Key Terms
References
Chapter 13: Describing Data
Descriptive Statistics and Exploratory Data Analysis
Organizing Your Data
Organizing Your Data for Computer Entry
Entering Your Data
Graphing Your Data
Elements of a Graph
Bar Graphs
Line Graphs
Scatter Plots
Pie Graphs
The Importance of Graphing Data
The Frequency Distribution
Displaying Distributions
Examining Your Distribution
Descriptive Statistics: Measures of Center and Spread
Measures of Center
Measures of Spread
Boxplots and the Five-Number Summary
Measures of Association, Regression, and Related Topics
The Pearson Product-Moment Correlation Coefficient
The Point-Biserial Correlation
The Spearman Rank-Order Correlation
The Phi Coefficient
Linear Regression and Prediction
The Coefficient of Determination
The Correlation Matrix
Multivariate Correlational Techniques
Summary
Key Terms
References
Chapter 14: Using Inferential Statistics
Inferential Statistics: Basic Concepts
From Samples to Populations
Sampling Error
Sampling Distributions
Standard Error
Degrees of Freedom
Estimation
The Dance of the Confidence Intervals
Sample Size and the Margin of Error
Estimation for a Two-Group Experiment
Null Hypothesis Significance Testing (NHST)
Statistical Errors
Determining Statistical Significance
One-Tailed Versus Two-Tailed Tests
Statistical Power
Statistical Versus Practical Significance
Recent Changes in Reporting Practices
Balancing Type I Versus Type II Errors
Parametric Statistical Tests
Assumptions Underlying a Parametric Statistic
Inferential Statistics with Two Samples
The t Test
The z Test for the Difference Between Two Proportions
Beyond Two Groups: Analysis of Variance (ANOVA)
The One-Factor Between-Subjects ANOVA
The One-Factor Within-Subjects ANOVA
The Two-Factor Between-Subjects ANOVA
The Two-Factor Within-Subjects ANOVA
Mixed Designs
Higher-Order and Special-Case ANOVAs
ANOVA: Summing Up
Nonparametric Statistical Tests
Chi-Square
The Mann–Whitney U Test
The Wilcoxon Signed Ranks Test
Parametric Versus Nonparametric Statistics
Data Transformations
A Bayesian Approach to Hypothesis Testing
NHST and the Replication Crisis
Suspect Practices
Addressing the Replication Crisis: Open Science and the “New Statistics”
Summary
Key Terms
References
Chapter 15: Using Multivariate Design and Analysis
Correlational and Experimental Multivariate Designs
Correlational Multivariate Design
Experimental Multivariate Design
Assumptions and Requirements of Multivariate Statistics
Linearity
Outliers
Normality and Homoscedasticity
Multicollinearity
Error of Measurement
Sample Size
Correlational Multivariate Statistical Tests
Factor Analysis
Partial and Part Correlations
Multiple Regression
Discriminant Analysis
Canonical Correlation
Experimental Multivariate Statistical Tests
Multivariate Analysis of Variance
Multiway Frequency Analysis
Multivariate Statistical Techniques and Causal Modeling
Path Analysis
Structural Equation Modeling
Multivariate Analysis: A Cautionary Note
Summary
Key Terms
References
Chapter 16: Reporting Your Research Results
APA Writing Style
Writing an APA-Style Research Report
Getting Ready to Write
Parts and Order of Manuscript Sections
The Title Page
The Abstract
The Introduction
The Method Section
The Results or Findings Section
The Discussion Section
The Reference Section
Footnotes
Tables
Figures
Elements of APA style
Citing References in Your Report
Citing Quoted Material
Using Numbers in the Text
Avoiding Biased Language
Expression, Organization, and Style
Precision and Clarity of Expression
Economy of Expression
Organization
Style
Making It Work
Avoiding Plagiarism and Lazy Writing
Telling the World About Your Results
Publishing Your Results
Paper Presentations
The Ethics of Reporting or Publishing Your Results
Summary
Key Terms
References
Glossary
Name Index
Subject Index