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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.

 

 
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

Supplements

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This book will be a useful addition to the reading lists for two unit exploring evidence-based practice and the creation of evidence in clinical practice.

Dr Leslie Gelling
Faculty of Health & Social Sciences(Nursing), Bournemouth University
January 29, 2023

I considered may different texts. This seemed to cover all required topics for Research Methods in Psychology. It is comprehensive and well-written

Dr Jeffrey D Stone
Sociology Dept, California St Univ-Los Angeles
January 12, 2022
Key features

NEW TO THIS EDITION:

  • Expanded coverage of Big Data includes an overview of how to use big data methods and a new focus on the crucial ethical challenges of obtaining and using big data.
  • A new focus on the variety and challenges of using public and research data includes data on COVID.
  • New and updated issues in Sampling, especially online sampling and nonresponse problems, provide students with the latest tools.
  • A thoroughly revised chapter on Theory, Models, and Research Questions uses community policing to demonstrate the value of revising logic models in light of research.
  • New examples and clarified explanations have been added to better teach one of the most important tools in causality in the chapter on Using Regression to Estimate Causal Effects.
  • Figures now maintain similar colors for independent variables, dependent variables, etc. across the book to help students identify these elements in each part of the research process.
  • The most current research in the field ensures the most up-to-date methods, including online surveys, recent research on when and how control variables studies with observational data can reproduce randomized experiment results, and the “Big Data" revolution.
  • New and updated examples apply research to a range of important social and policy issues.
KEY FEATURES:
  • Current methodological techniques used in interdisciplinary research are addressed throughout.
  • Many interesting, current examples of policy-relevant studies illustrate key research methods.
  • Strategies for both description and causal estimation are included and emphasize the distinction between the two.
  • Advanced methodological ideas and techniques are explained in a clear and accessible manner.

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