Research Methods in Practice
Strategies for Description and Causation
Third Edition
Dahlia K. Remler
- Baruch College, CUNY, USA
Gregg G. Van Ryzin
- Rutgers University, Newark, USA
If you’re in North America, please visit our Sage College Publishing website to purchase or sample this book:
Go to College Publishing WebsiteDescription
Thoroughly updated to reflect changes in both research and methods, this Third Edition of Remler and Van Ryzin’s innovative, standard-setting text is imbued with a deep commitment to making social and policy research methods accessible and meaningful. Research Methods in Practice: Strategies for Description and Causation motivates readers to examine the logic and limits of social science research from academic journals and government reports. A central theme of causation versus description runs through the text, emphasizing the idea that causal research is essential to understanding the origins of social problems and their potential solutions. Readers will find excitement in the research experience as the best hope for improving the world in which we live, while also acknowledging the trade-offs and uncertainties in real-world research.
Contents
Preface
Preface
Acknowledgments
Acknowledgments
About the Authors
About the Authors
PART I: FOUNDATIONS
- Chapter 1. Research in the Real World
- Learning Objectives
- Do Methods Matter?
- Research, Policy, and Practice
- Evidence Can Mislead
- What Is Research?
- Descriptive and Causal Research
- Epistemology: Ways of Knowing
- Approaching Research From Different Angles
- Ethics of Research
- Conclusion: The Road Ahead
- Exercises
- Chapter 2. Theory, Models, and Research Questions
- Learning Objectives
- Community Policing Comes to Portland
- What Is a Theory?
- What Is a Model?
- Logic Models: Mechanisms of Programs
- Alternative Perspectives on Theory in Social Research
- How to Find and Focus Research Questions
- Conclusion: Theories Are Practical
- Chapter 3. Qualitative Research
- Learning Objectives
- Fighting Malaria in Kenya
- What Is Qualitative Research?
- Existing Qualitative Data
- Qualitative Interviews
- Focus Groups
- Qualitative Observation
- Participant Observation and Ethnography
- Case Study Research
- Qualitative Data Analysis
- The Qualitative-Quantitative Debate
- Ethics in Qualitative Research
- Conclusion: Matching Methods to Questions
- Exercises
PART II: STRATEGIES FOR DESCRIPTION
- Chapter 4. Measurement
- Learning Objectives
- The U.S. Poverty Measure
- What Is Measurement?
- Conceptualization
- Operationalization
- Validity
- Criterion-Related Validity
- Measurement Error
- Reliability
- Validity and Reliability in Qualitative Research
- Levels of Measurement
- Measurement in the Real World: Trade-offs and Choices
- Conclusion: Measurement Matters
- Exercises
- Chapter 5. Sampling
- Learning Objectives
- Gauging the Fallout From Hurricane Katrina
- Generalizability
- Basic Sampling Concepts
- Problems and Biases in Sampling
- Nonprobability Sampling
- Random (Probability) Sampling
- Sampling Distributions, Standard Errors, and Confidence Intervals
- Sampling in Practice
- Sampling and Generalizability: A Summary
- Exercises
- Chapter 6. Secondary Data
- Learning Objectives
- Tracking a Global Pandemic
- Quantitative Data Forms and Structures
- Administrative Records
- Aggregate Data Tables
- Public Use Microdata
- Secondary Qualitative Data
- Big Data
- Linking Data
- Some Limitations of Secondary Data
- Conclusion
- Exercises
- Chapter 7. Surveys and Other Primary Data
- Learning Objectives
- Taking the Nation’s Economic Pulse
- When Should You Do a Survey?
- Steps in the Survey Research Process
- Modes of Survey Data Collection
- Crafting a Questionnaire
- Ethics of Survey Research
- Other Ways to Collect Primary Data
- Conclusion
- Exercises
PART III: STATISTICAL TOOLS AND INTERPRETATIONS
- Chapter 8. Making Sense of the Numbers
- Learning Objectives
- “Last Weekend I Walked Eight”
- Units, Rates, and Ratios
- Statistics Starting Point: Variables in a Data Set
- Distributions
- Measures of Center: Mean and Median
- Measures of Spread and Variation
- Relationships Between Categorical Variables
- Relationships Between Quantitative Variables: Scatterplots and Correlation
- Simple Regression: Best-Fit Straight Line
- Practical Significance
- Statistical Software
- Conclusion: Tools for Description and Causation
- Exercises
- Chapter 9. Making Sense of Inferential Statistics
- Learning Objectives
- But Is It Significant?
- Statistical Inference: What’s It Good For?
- The Sampling Distribution: Foundation of Statistical Inference
- Confidence Intervals
- Significance Tests
- Statistical Significance, Practical Significance, and Power
- Issues and Extensions of Statistical Inference
- Conclusion
- Exercises
- Chapter 10. Making Sense of Multivariate Statistics
- Learning Objectives
- Multiple Regression: The Basics
- Inference for Regression
- Categorical Independent Variables
- Interactions in Regression
- Functional Form and Transformations in Regression
- Categorical Variables as Dependent Variables in Regression
- Which Statistical Methods Can I Use?
- Other Multivariate Methods
- Conclusion
- Exercises
PART IV: STRATEGIES FOR CAUSATION
- Chapter 11. Causation
- Learning Objectives
- Family Dinners and Teenage Substance Abuse
- Alternative Explanations of a Correlation
- Causal Mechanisms
- Evidence of Causation: Some Critical Clues
- Self-Selection and Endogeneity
- The Counterfactual Definition of Causation
- Experimentation and Exogeneity: Making Things Happen
- Conclusion: Tools to Probe Causation
- Exercises
- Chapter 12. Observational Studies
- Learning Objectives
- Private Versus Public Schools
- What Is an Observational Study?
- Control Variables
- Matching
- Control Variables: An Empirical Example
- How to Choose Control Variables
- Epidemiological Approaches to Observational Studies
- Conclusion: Observational Studies in Perspective
- Exercises
- Chapter 13. Using Regression to Estimate Causal Effects
- Learning Objectives
- Cigarette Taxes and Smoking
- From Stratification to Multiple Regression
- Does Greenery Affect Birth Outcomes?
- Further Topics in Regression for Estimating Causal Effects
- Control Variables With Exogenous Independent Variables: The Gender Earnings Gap
- Other Multivariate Techniques for Observational Studies
- Conclusion: A Widely Used Strategy, With Drawbacks
- Exercises
- Chapter 14. Randomized Experiments
- Learning Objectives
- Time Limits on Welfare
- Random Assignment: Creating Statistical Equivalence
- The Logic of Randomized Experiments: Exogeneity Revisited
- The Settings of Randomized Experiments
- Generalizability of Randomized Experiments
- Variations on the Design of Experiments
- Artifacts in Experiments
- Analysis of Randomized Experiments
- Ethics of Randomized Experiments
- Qualitative Methods and Randomized Experiments
- Conclusion: A Gold Standard, With Limitations
- Exercises
- Chapter 15. Natural and Quasi Experiments
- Learning Objectives
- A Casino Benefits the Mental Health of Cherokee Children
- What Are Natural and Quasi Experiments?
- Internal Validity of Natural and Quasi Experiments
- Generalizability of Natural and Quasi Experiments
- Types of Natural and Quasi Experimental Studies
- Difference-in-Differences Strategy
- Instrumental Variables and Regression Discontinuity
- Regression Discontinuity
- Ethics of Quasi and Natural Experiments
- Conclusion
- Exercises
PART V: CONTEXT AND COMMUNICATION
- Chapter 16. The Politics, Production, and Ethics of Research
- Learning Objectives
- Risking Your Baby’s Health
- From Research to Policy
- The Production of Research
- Making Research Ethical
- Making Research Open and Transparent
- Conclusion
- Exercises
- Chapter 17. How to Find, Review, and Present Research
- Learning Objectives
- Where to Find Research
- How to Search for Studies
- How to Write a Literature Review
- How to Communicate Your Own Research
- How to Publish Your Research
- Conclusion
- Exercises
Glossary
Glossary
References
References
Index
Index
Additional materials
Description
Thoroughly updated to reflect changes in both research and methods, this Third Edition of Remler and Van Ryzin’s innovative, standard-setting text is imbued with a deep commitment to making social and policy research methods accessible and meaningful. Research Methods in Practice: Strategies for Description and Causation motivates readers to examine the logic and limits of social science research from academic journals and government reports. A central theme of causation versus description runs through the text, emphasizing the idea that causal research is essential to understanding the origins of social problems and their potential solutions. Readers will find excitement in the research experience as the best hope for improving the world in which we live, while also acknowledging the trade-offs and uncertainties in real-world research.
Contents
Preface
Preface
Acknowledgments
Acknowledgments
About the Authors
About the Authors
PART I: FOUNDATIONS
- Chapter 1. Research in the Real World
- Learning Objectives
- Do Methods Matter?
- Research, Policy, and Practice
- Evidence Can Mislead
- What Is Research?
- Descriptive and Causal Research
- Epistemology: Ways of Knowing
- Approaching Research From Different Angles
- Ethics of Research
- Conclusion: The Road Ahead
- Exercises
- Chapter 2. Theory, Models, and Research Questions
- Learning Objectives
- Community Policing Comes to Portland
- What Is a Theory?
- What Is a Model?
- Logic Models: Mechanisms of Programs
- Alternative Perspectives on Theory in Social Research
- How to Find and Focus Research Questions
- Conclusion: Theories Are Practical
- Chapter 3. Qualitative Research
- Learning Objectives
- Fighting Malaria in Kenya
- What Is Qualitative Research?
- Existing Qualitative Data
- Qualitative Interviews
- Focus Groups
- Qualitative Observation
- Participant Observation and Ethnography
- Case Study Research
- Qualitative Data Analysis
- The Qualitative-Quantitative Debate
- Ethics in Qualitative Research
- Conclusion: Matching Methods to Questions
- Exercises
PART II: STRATEGIES FOR DESCRIPTION
- Chapter 4. Measurement
- Learning Objectives
- The U.S. Poverty Measure
- What Is Measurement?
- Conceptualization
- Operationalization
- Validity
- Criterion-Related Validity
- Measurement Error
- Reliability
- Validity and Reliability in Qualitative Research
- Levels of Measurement
- Measurement in the Real World: Trade-offs and Choices
- Conclusion: Measurement Matters
- Exercises
- Chapter 5. Sampling
- Learning Objectives
- Gauging the Fallout From Hurricane Katrina
- Generalizability
- Basic Sampling Concepts
- Problems and Biases in Sampling
- Nonprobability Sampling
- Random (Probability) Sampling
- Sampling Distributions, Standard Errors, and Confidence Intervals
- Sampling in Practice
- Sampling and Generalizability: A Summary
- Exercises
- Chapter 6. Secondary Data
- Learning Objectives
- Tracking a Global Pandemic
- Quantitative Data Forms and Structures
- Administrative Records
- Aggregate Data Tables
- Public Use Microdata
- Secondary Qualitative Data
- Big Data
- Linking Data
- Some Limitations of Secondary Data
- Conclusion
- Exercises
- Chapter 7. Surveys and Other Primary Data
- Learning Objectives
- Taking the Nation’s Economic Pulse
- When Should You Do a Survey?
- Steps in the Survey Research Process
- Modes of Survey Data Collection
- Crafting a Questionnaire
- Ethics of Survey Research
- Other Ways to Collect Primary Data
- Conclusion
- Exercises
PART III: STATISTICAL TOOLS AND INTERPRETATIONS
- Chapter 8. Making Sense of the Numbers
- Learning Objectives
- “Last Weekend I Walked Eight”
- Units, Rates, and Ratios
- Statistics Starting Point: Variables in a Data Set
- Distributions
- Measures of Center: Mean and Median
- Measures of Spread and Variation
- Relationships Between Categorical Variables
- Relationships Between Quantitative Variables: Scatterplots and Correlation
- Simple Regression: Best-Fit Straight Line
- Practical Significance
- Statistical Software
- Conclusion: Tools for Description and Causation
- Exercises
- Chapter 9. Making Sense of Inferential Statistics
- Learning Objectives
- But Is It Significant?
- Statistical Inference: What’s It Good For?
- The Sampling Distribution: Foundation of Statistical Inference
- Confidence Intervals
- Significance Tests
- Statistical Significance, Practical Significance, and Power
- Issues and Extensions of Statistical Inference
- Conclusion
- Exercises
- Chapter 10. Making Sense of Multivariate Statistics
- Learning Objectives
- Multiple Regression: The Basics
- Inference for Regression
- Categorical Independent Variables
- Interactions in Regression
- Functional Form and Transformations in Regression
- Categorical Variables as Dependent Variables in Regression
- Which Statistical Methods Can I Use?
- Other Multivariate Methods
- Conclusion
- Exercises
PART IV: STRATEGIES FOR CAUSATION
- Chapter 11. Causation
- Learning Objectives
- Family Dinners and Teenage Substance Abuse
- Alternative Explanations of a Correlation
- Causal Mechanisms
- Evidence of Causation: Some Critical Clues
- Self-Selection and Endogeneity
- The Counterfactual Definition of Causation
- Experimentation and Exogeneity: Making Things Happen
- Conclusion: Tools to Probe Causation
- Exercises
- Chapter 12. Observational Studies
- Learning Objectives
- Private Versus Public Schools
- What Is an Observational Study?
- Control Variables
- Matching
- Control Variables: An Empirical Example
- How to Choose Control Variables
- Epidemiological Approaches to Observational Studies
- Conclusion: Observational Studies in Perspective
- Exercises
- Chapter 13. Using Regression to Estimate Causal Effects
- Learning Objectives
- Cigarette Taxes and Smoking
- From Stratification to Multiple Regression
- Does Greenery Affect Birth Outcomes?
- Further Topics in Regression for Estimating Causal Effects
- Control Variables With Exogenous Independent Variables: The Gender Earnings Gap
- Other Multivariate Techniques for Observational Studies
- Conclusion: A Widely Used Strategy, With Drawbacks
- Exercises
- Chapter 14. Randomized Experiments
- Learning Objectives
- Time Limits on Welfare
- Random Assignment: Creating Statistical Equivalence
- The Logic of Randomized Experiments: Exogeneity Revisited
- The Settings of Randomized Experiments
- Generalizability of Randomized Experiments
- Variations on the Design of Experiments
- Artifacts in Experiments
- Analysis of Randomized Experiments
- Ethics of Randomized Experiments
- Qualitative Methods and Randomized Experiments
- Conclusion: A Gold Standard, With Limitations
- Exercises
- Chapter 15. Natural and Quasi Experiments
- Learning Objectives
- A Casino Benefits the Mental Health of Cherokee Children
- What Are Natural and Quasi Experiments?
- Internal Validity of Natural and Quasi Experiments
- Generalizability of Natural and Quasi Experiments
- Types of Natural and Quasi Experimental Studies
- Difference-in-Differences Strategy
- Instrumental Variables and Regression Discontinuity
- Regression Discontinuity
- Ethics of Quasi and Natural Experiments
- Conclusion
- Exercises
PART V: CONTEXT AND COMMUNICATION
- Chapter 16. The Politics, Production, and Ethics of Research
- Learning Objectives
- Risking Your Baby’s Health
- From Research to Policy
- The Production of Research
- Making Research Ethical
- Making Research Open and Transparent
- Conclusion
- Exercises
- Chapter 17. How to Find, Review, and Present Research
- Learning Objectives
- Where to Find Research
- How to Search for Studies
- How to Write a Literature Review
- How to Communicate Your Own Research
- How to Publish Your Research
- Conclusion
- Exercises
Glossary
Glossary
References
References
Index
Index
Additional materials
Research Methods in Practice
Strategies for Description and Causation
August 2021 | 728 pages | Sage US
| Format | Published Date | ISBN | Price |
|---|
Thoroughly updated to reflect changes in both research and methods, this Third Edition of Remler and Van Ryzin’s innovative, standard-setting text is imbued with a deep commitment to making social and policy research methods accessible and meaningful. Research Methods in Practice: Strategies for Description and Causation motivates readers to examine the logic and limits of social science research from academic journals and government reports. A central theme of causation versus description runs through the text, emphasizing the idea that causal research is essential to understanding the origins of social problems and their potential solutions. Readers will find excitement in the research experience as the best hope for improving the world in which we live, while also acknowledging the trade-offs and uncertainties in real-world research.
Table Of Contents:
- Preface
- Acknowledgments
- About the Authors
- PART I: FOUNDATIONS
- Chapter 1. Research in the Real World
- Learning Objectives
- Do Methods Matter?
- Research, Policy, and Practice
- Evidence Can Mislead
- What Is Research?
- Descriptive and Causal Research
- Epistemology: Ways of Knowing
- Approaching Research From Different Angles
- Ethics of Research
- Conclusion: The Road Ahead
- Exercises
- Chapter 2. Theory, Models, and Research Questions
- Learning Objectives
- Community Policing Comes to Portland
- What Is a Theory?
- What Is a Model?
- Logic Models: Mechanisms of Programs
- Alternative Perspectives on Theory in Social Research
- How to Find and Focus Research Questions
- Conclusion: Theories Are Practical
- Chapter 3. Qualitative Research
- Learning Objectives
- Fighting Malaria in Kenya
- What Is Qualitative Research?
- Existing Qualitative Data
- Qualitative Interviews
- Focus Groups
- Qualitative Observation
- Participant Observation and Ethnography
- Case Study Research
- Qualitative Data Analysis
- The Qualitative-Quantitative Debate
- Ethics in Qualitative Research
- Conclusion: Matching Methods to Questions
- Exercises
- PART II: STRATEGIES FOR DESCRIPTION
- Chapter 4. Measurement
- Learning Objectives
- The U.S. Poverty Measure
- What Is Measurement?
- Conceptualization
- Operationalization
- Validity
- Criterion-Related Validity
- Measurement Error
- Reliability
- Validity and Reliability in Qualitative Research
- Levels of Measurement
- Measurement in the Real World: Trade-offs and Choices
- Conclusion: Measurement Matters
- Exercises
- Chapter 5. Sampling
- Learning Objectives
- Gauging the Fallout From Hurricane Katrina
- Generalizability
- Basic Sampling Concepts
- Problems and Biases in Sampling
- Nonprobability Sampling
- Random (Probability) Sampling
- Sampling Distributions, Standard Errors, and Confidence Intervals
- Sampling in Practice
- Sampling and Generalizability: A Summary
- Exercises
- Chapter 6. Secondary Data
- Learning Objectives
- Tracking a Global Pandemic
- Quantitative Data Forms and Structures
- Administrative Records
- Aggregate Data Tables
- Public Use Microdata
- Secondary Qualitative Data
- Big Data
- Linking Data
- Some Limitations of Secondary Data
- Conclusion
- Exercises
- Chapter 7. Surveys and Other Primary Data
- Learning Objectives
- Taking the Nation’s Economic Pulse
- When Should You Do a Survey?
- Steps in the Survey Research Process
- Modes of Survey Data Collection
- Crafting a Questionnaire
- Ethics of Survey Research
- Other Ways to Collect Primary Data
- Conclusion
- Exercises
- PART III: STATISTICAL TOOLS AND INTERPRETATIONS
- Chapter 8. Making Sense of the Numbers
- Learning Objectives
- “Last Weekend I Walked Eight”
- Units, Rates, and Ratios
- Statistics Starting Point: Variables in a Data Set
- Distributions
- Measures of Center: Mean and Median
- Measures of Spread and Variation
- Relationships Between Categorical Variables
- Relationships Between Quantitative Variables: Scatterplots and Correlation
- Simple Regression: Best-Fit Straight Line
- Practical Significance
- Statistical Software
- Conclusion: Tools for Description and Causation
- Exercises
- Chapter 9. Making Sense of Inferential Statistics
- Learning Objectives
- But Is It Significant?
- Statistical Inference: What’s It Good For?
- The Sampling Distribution: Foundation of Statistical Inference
- Confidence Intervals
- Significance Tests
- Statistical Significance, Practical Significance, and Power
- Issues and Extensions of Statistical Inference
- Conclusion
- Exercises
- Chapter 10. Making Sense of Multivariate Statistics
- Learning Objectives
- Multiple Regression: The Basics
- Inference for Regression
- Categorical Independent Variables
- Interactions in Regression
- Functional Form and Transformations in Regression
- Categorical Variables as Dependent Variables in Regression
- Which Statistical Methods Can I Use?
- Other Multivariate Methods
- Conclusion
- Exercises
- PART IV: STRATEGIES FOR CAUSATION
- Chapter 11. Causation
- Learning Objectives
- Family Dinners and Teenage Substance Abuse
- Alternative Explanations of a Correlation
- Causal Mechanisms
- Evidence of Causation: Some Critical Clues
- Self-Selection and Endogeneity
- The Counterfactual Definition of Causation
- Experimentation and Exogeneity: Making Things Happen
- Conclusion: Tools to Probe Causation
- Exercises
- Chapter 12. Observational Studies
- Learning Objectives
- Private Versus Public Schools
- What Is an Observational Study?
- Control Variables
- Matching
- Control Variables: An Empirical Example
- How to Choose Control Variables
- Epidemiological Approaches to Observational Studies
- Conclusion: Observational Studies in Perspective
- Exercises
- Chapter 13. Using Regression to Estimate Causal Effects
- Learning Objectives
- Cigarette Taxes and Smoking
- From Stratification to Multiple Regression
- Does Greenery Affect Birth Outcomes?
- Further Topics in Regression for Estimating Causal Effects
- Control Variables With Exogenous Independent Variables: The Gender Earnings Gap
- Other Multivariate Techniques for Observational Studies
- Conclusion: A Widely Used Strategy, With Drawbacks
- Exercises
- Chapter 14. Randomized Experiments
- Learning Objectives
- Time Limits on Welfare
- Random Assignment: Creating Statistical Equivalence
- The Logic of Randomized Experiments: Exogeneity Revisited
- The Settings of Randomized Experiments
- Generalizability of Randomized Experiments
- Variations on the Design of Experiments
- Artifacts in Experiments
- Analysis of Randomized Experiments
- Ethics of Randomized Experiments
- Qualitative Methods and Randomized Experiments
- Conclusion: A Gold Standard, With Limitations
- Exercises
- Chapter 15. Natural and Quasi Experiments
- Learning Objectives
- A Casino Benefits the Mental Health of Cherokee Children
- What Are Natural and Quasi Experiments?
- Internal Validity of Natural and Quasi Experiments
- Generalizability of Natural and Quasi Experiments
- Types of Natural and Quasi Experimental Studies
- Difference-in-Differences Strategy
- Instrumental Variables and Regression Discontinuity
- Regression Discontinuity
- Ethics of Quasi and Natural Experiments
- Conclusion
- Exercises
- PART V: CONTEXT AND COMMUNICATION
- Chapter 16. The Politics, Production, and Ethics of Research
- Learning Objectives
- Risking Your Baby’s Health
- From Research to Policy
- The Production of Research
- Making Research Ethical
- Making Research Open and Transparent
- Conclusion
- Exercises
- Chapter 17. How to Find, Review, and Present Research
- Learning Objectives
- Where to Find Research
- How to Search for Studies
- How to Write a Literature Review
- How to Communicate Your Own Research
- How to Publish Your Research
- Conclusion
- Exercises
- Glossary
- References
- Index