Research Methods for Public Administrators

<p>As in previous editions, this highly practical book is written with beginning MPA students and practitioners in mind. It focuses on the interpretation and use of research findings, not just number crunching. It covers the entire research process, from initial questions to final report, in clear, jargon-free language, and includes numerous easy-to-understand examples and exercises that provide opportunities for concrete applications of the concepts. It is solidly grounded in public administration and recognizes both the promise and limitations of research within a political environment.<br><br>Key features of the book:<br><br>--It is highly practical and written to accommodate a mix of readers: those who want to become analysts, managers who will oversee research contracts, and citizens who need to know whether to believe the facts and data they read in today's news;<br><br>--It minimizes the use of jargon and explains difficult concepts in clear language. Plentiful end-of-chapter exercises provide opportunities for concrete application of the concepts;<br><br>--Key points are highlighted as "takeaway lessons" so readers are reminded about what really matters. The tough questions to ask are suggested in every chapter;<br><br>--Examples and applications are used throughout the book to illustrate concepts and add topical interest;<br><br>--It covers the entire research process, from initial questions to the final report. <br><br>This book demystifies and makes practical the research every public administrator and policy analyst needs to do the job well. Online instructor's materials, including a Test Bank, PowerPoint slides, and a Survey and Documental Analysis (SDA) guide, are also available to adopters.</p> <p>List of Illustrations<br>Preface and Acknowledgments</p><p><b>1. Introduction: Research Methods for Public Administrators</b><br>Overview Goals: Research as a Critical Thinking Tool Research in the Public Sector What Is Research? Types of Research Ethics and Principles of Good Research<br>Overview of This Book<br>Exercises<br><b>2. Basic Research Concepts</b><br>Overview<br>The Secret Language of Social Science Theory Hypothesis in Its Many Forms Variables Values Levels of Measurement Determining Causality Independent and Dependent Variables Control Variables Direction of Relationships Program Evaluation: Research in the Public Sector<br>Using Models for a Holistic View of Relationships<br>The Logic Model<br>Applying the Logic Model<br>Conclusion<br>Exercises<br><b>3. What Is the Question?</b><br>Overview<br>Determining the Research Question<br>Learning from Others<br>Engaging the Stakeholders<br>Working Together<br>Types of Questions Descriptive Questions Normative Questions Relationship Questions Conclusion<br>Exercises<br><b>4. Identifying Measures and Measurement Strategy</b><br>Overview<br>Defining Key Terms Conceptual Definitions Operational Definitions Setting Boundaries<br>Valid and Reliable Measures Validity Reliability Why Measurement Matters<br>Conclusion<br>Exercises<br><b>5. Designs for Research: The <i>X</i>s and <i>O</i>s Framework</b><br>Overview<br>Designing an Experiment<br>Applying the Design Elements: The <i>X</i>s and <i>O</i>s Framework Nonexperimental Design Quasi-Experimental Design Classic Experimental Design Design Variations Using Statistical Controls to Create Comparison Groups Longitudinal Studies Internal Validity<br>Why Validity Matters<br>External Validity<br>Conclusion<br>Exercises<br><br><b>6. Other Research Approaches</b><br>Overview<br>Secondary Analysis of Data<br>Evaluation Synthesis (Meta-Analysis)<br>Content Analysis<br>Survey Research<br>Case Studies<br>Cost-Benefit Analysis<br>Conclusion<br>Exercises<br><br><b>7. Data Collection I: Available Data and Observation</b><br>Overview<br>Data Collection: The Degree of Structure<br>Available Data<br>Data Collection Instruments<br>Observation<br>Obtrusive and Unobtrusive Data Collection<br>The Design Matrix<br>Conclusion<br>Exercises<br><br><b>8. Data Collection II: Interviews and Focus Groups</b><br>Overview<br>General Guidelines About Choosing the Appropriate Method<br>Encouraging Participation<br>In-Person Interviews<br>Focus Groups<br>Other Group Data Collection: Expert Panels, Public Hearings<br>Conclusion<br>Exercises<br><br><b>9. Data Collection III: Surveys</b><br>Overview<br>Basic Methods<br>Response Rates<br>Telephone Surveys<br>Mail Surveys<br>Cyber-Research: E-mail and Web-Based Surveys<br>Developing Closed-Ended Questions<br>Using One-Way and Two-Way Intensity Scales<br>Ranking Questions<br>Demographic Questions<br>Conclusion<br>Exercises<br><b>10. Sampling Demystified</b><br>Overview<br>Sampling Jargon<br>Random and Nonrandom Samples Random Samples Nonrandom Samples Random Samples: The Options Simple Random Sample Systematic Random Sample Stratified Random Sample Proportional Stratified Sample Disproportionate Stratified Sample Cluster Sample Nonrandom Samples: The Options<br>Determining Sample Size<br>Nonsampling Errors<br>Conclusion<br>Exercises<br><br><b>11. Qualitative Data Analysis</b><br>Overview<br>Analyzing Qualitative Data<br>Identifying Themes and Quotes<br>Working with Qualitative Data<br>Conclusion<br>Exercises<br><b>12. Data Analysis for Description</b><br>Overview<br>Simple Descriptive Statistics in Public Administration<br>Commonly Used Descriptive Statistics Counts Percents Rates Ratios Rates of Change Distributions Measures of Central Tendency Which Measure to Use? Comparison of Means Measures of Dispersion<br>Conclusion<br>Exercises<br><br><b>13. Analyzing Survey Scales</b><br>Overview<br>Handling Exits and the Middle of a Five-Point Scale<br>Setting Benchmarks and Extreme Analysis<br>Handling the Middle Category in One-Way Intensity Scales<br>Should Means Be Used with Nominal and Ordinal Scales?<br>The Analytical Tool: Cross Tabulations<br>Conclusion<br>Exercises<br><br><b>14. Data Analysis: Exploring Relationships</b><br>Overview<br>Using Crosstabs to Examine Relationships<br>Controlling for a Third Variable<br>Exploring Relationships: Comparison of Means and Medians<br>Measures of Association<br>Frequently Used Measures of Association<br>Working with Interval or Ratio Data<br>Conclusion<br>Exercises<br><b>15. Data Analysis: Regression</b><br>Overview<br>Bivariate Regression: Key Elements<br>Using Bivariate Regression Analysis: Sunshine and Tourism<br>Multiple Regression Beta Weights: Relative Predictive Strength Regression in the News<br>Why Did the Violent Crime Rate Drop After 1991?<br>Conclusion<br>Exercises<br><b>16. Data Analysis Using Inferential Statistics</b><br>Overview<br>Statistical Significance: Basic Concepts<br>The Logic of Statistical Significance Testing<br>Errors in Tests for Statistical Significance<br>Common Tests for Statistical Significance Chi-Square<i> t</i>-Tests: Analyzing Difference in Means Analysis of Variance Tests for Statistical Significance in Regression Analysis<br>Reporting Results of Statistical Significance<br>Population Estimates and Confidence Intervals<br>Conclusion<br>Exercises<br><br><b>17. Communicating Research Results</b><br>Overview<br>Effectively Reporting Results<br>Reporting Data<br>General Guide for Communicating Research Results<br>Guide for Writing an Executive Summary<br>Guide for Writing a Formal Report<br>Guide for Using Charts and Tables<br>Guide for Oral Presentations<br>Presenting Unwelcome Information<br>Making Sense of Research Results<br>Conclusion<br>Exercises<br><b>18. Conclusion: Research at the Intersection of Politics and Administration</b><br>Overview<br>The Research Process Revisited Planning Doing Reporting Ethics and Social Justice<br>Managing Research Projects<br>Assessing Credibility<br>The Limitations of Science<br>The Intersection of Research, Politics, and Administration<br>Closing Observations<br>Exercises<br><br>Appendix A. Mathematical Formulas for Selected Statistics<br>Appendix B. Statistics as a Second Language<br>Appendix C. Bibliography<br>Appendix D. Logic Model Template<br>Appendix E. The Generic Design Matrix<br><br>Index<br>About the Author</p>