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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.


About the Authors
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


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


Chapter 4. Measurement
Learning Objectives

The U.S. Poverty Measure

What Is Measurement?




Criterion-Related Validity

Measurement Error


Validity and Reliability in Qualitative Research

Levels of Measurement

Measurement in the Real World: Trade-offs and Choices

Conclusion: Measurement Matters


Chapter 5. Sampling
Learning Objectives

Gauging the Fallout From Hurricane Katrina


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


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



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



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


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


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



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



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


Chapter 12. Observational Studies
Learning Objectives

Private Versus Public Schools

What Is an Observational Study?

Control Variables


Control Variables: An Empirical Example

How to Choose Control Variables

Epidemiological Approaches to Observational Studies

Conclusion: Observational Studies in Perspective


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


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


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



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



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





Instructor Resource Site

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  • Editable chapter-specific PowerPoint® slides
  • Instructor’s Manual with activities and suggested assignments
  • Datasets
  • All tables and figures from the textbook 
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Student Study Site


The open-access Student Study Site makes it easy for students to maximize their study time, anywhere, anytime. It offers datasets and videos from the authors of key examples from the book.

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


  • 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.
  • 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.

For instructors

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