Research Methods in Practice: Strategies for Description and Causation

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

About the Author :
Dahlia K. Remler is Professor at the School of Public Affairs, Baruch College, and the Department of Economics, Graduate Center, both of the City University of New York. She is also a Research Associate at the National Bureau of Economic Research. Dahlia has been in an unusual mix of disciplinary and interdisciplinary settings. She received a BS in electrical engineering from the University of California at Berkeley, a DPhil in physical chemistry from Oxford University—while a Marshall Scholar—and a PhD in economics from Harvard University. During the Clinton administration’s health care reform efforts, Dahlia held a fellowship at the Brookings Institution to finish her dissertation on health care cost containment. She then held a postdoctoral research fellowship at Harvard Medical School, followed by assistant professorships at Tulane’s and Columbia’s Schools of Public Health, prior to joining the faculty at Baruch. She enjoys comparing and contrasting how different disciplines see the same issues. Dahlia has published widely in a variety of areas in health care policy, including health care cost containment, information technology in health care, cigarette tax regressivity, simulation methods for health insurance take-up, and health insurance and health care markets. She has also recently started working on higher education and media issues. Her work has appeared in the Journal of Policy Analysis and Management, Health Affairs, the Quarterly Journal of Economics, the American Journal of Public Health, Medical Care Research and Review, and many other journals. She blogs on health care policy, higher education and other topics at DahliaRemler.com. Dahlia lives with her husband, Howard, in New York City, where they enjoy the city’s theaters, restaurants, and parks—and Dahlia enjoys being a complete amateur dancer in some of the city’s superb dance studios. Gregg G. Van Ryzin is Professor at the School of Public Affairs and Administration, Rutgers University—Newark. He received his BA in geography from Columbia University and his PhD in psychology from the City University of New York. During his doctoral training, he worked as a planner for a nonprofit housing and community development organization in New York City, and he completed his dissertation on low income housing for the elderly in Detroit. He next worked in Washington, D.C., for ICF Inc. and later Westat, Inc. on surveys and program evaluations for the U.S. Department of Housing and Urban Development and other federal agencies. In 1995, he joined the faculty of the School of Public Affairs, Baruch College, where he directed their Survey Research Unit for 8 years. In that role, he helped develop and direct the New York City Community Health Survey, a large-scale behavioral health survey for the city’s health department, and also played a key role in shaping and conducting the city’s survey of satisfaction with government services. He has spent time in Madrid, collaborating with researchers there on the analysis of surveys about public attitudes toward Spanish government policy. Gregg has published many scholarly articles on housing and welfare programs, survey and evaluation methods, and public opinion about government services and institutions. His work has appeared in the International Review of Administrative Sciences, the Journal of Policy Analysis and Management, the Journal of Public Administration Research and Theory, the Journal of Urban Affairs, Nonprofit and Voluntary Sector Quarterly, Public Administration Review, Public Management Review, Public Performance and Management Review, Urban Affairs Review, and other journals. Gregg lives in New York City with his wife, Ada (a history professor at NYU), and their daughters Alina and Lucia. They enjoy life in their Greenwich Village neighborhood, escaping on occasion to Spain, Miami, Maine, Cuba, and other interesting places in the world.