Research Methods for Public Administrators Third Edition

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.Key features of the book:--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;--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;--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;--Examples and applications are used throughout the book to illustrate concepts and add topical interest;--It covers the entire research process, from initial questions to the final report. 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.

List of IllustrationsPreface and Acknowledgments1. Introduction: Research Methods for Public AdministratorsOverview Goals: Research as a Critical Thinking Tool Research in the Public Sector What Is Research? Types of Research Ethics and Principles of Good ResearchOverview of This BookExercises2. Basic Research ConceptsOverviewThe 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 SectorUsing Models for a Holistic View of RelationshipsThe Logic ModelApplying the Logic ModelConclusionExercises3. What Is the Question?OverviewDetermining the Research QuestionLearning from OthersEngaging the StakeholdersWorking TogetherTypes of Questions Descriptive Questions Normative Questions Relationship Questions ConclusionExercises4. Identifying Measures and Measurement StrategyOverviewDefining Key Terms Conceptual Definitions Operational Definitions Setting BoundariesValid and Reliable Measures Validity Reliability Why Measurement MattersConclusionExercises5. Designs for Research: The Xs and Os FrameworkOverviewDesigning an ExperimentApplying the Design Elements: The Xs and Os Framework Nonexperimental Design Quasi-Experimental Design Classic Experimental Design Design Variations Using Statistical Controls to Create Comparison Groups Longitudinal Studies Internal ValidityWhy Validity MattersExternal ValidityConclusionExercises6. Other Research ApproachesOverviewSecondary Analysis of DataEvaluation Synthesis (Meta-Analysis)Content AnalysisSurvey ResearchCase StudiesCost-Benefit AnalysisConclusionExercises7. Data Collection I: Available Data and ObservationOverviewData Collection: The Degree of StructureAvailable DataData Collection InstrumentsObservationObtrusive and Unobtrusive Data CollectionThe Design MatrixConclusionExercises8. Data Collection II: Interviews and Focus GroupsOverviewGeneral Guidelines About Choosing the Appropriate MethodEncouraging ParticipationIn-Person InterviewsFocus GroupsOther Group Data Collection: Expert Panels, Public HearingsConclusionExercises9. Data Collection III: SurveysOverviewBasic MethodsResponse RatesTelephone SurveysMail SurveysCyber-Research: E-mail and Web-Based SurveysDeveloping Closed-Ended QuestionsUsing One-Way and Two-Way Intensity ScalesRanking QuestionsDemographic QuestionsConclusionExercises10. Sampling DemystifiedOverviewSampling JargonRandom 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 OptionsDetermining Sample SizeNonsampling ErrorsConclusionExercises11. Qualitative Data AnalysisOverviewAnalyzing Qualitative DataIdentifying Themes and QuotesWorking with Qualitative DataConclusionExercises12. Data Analysis for DescriptionOverviewSimple Descriptive Statistics in Public AdministrationCommonly Used Descriptive Statistics Counts Percents Rates Ratios Rates of Change Distributions Measures of Central Tendency Which Measure to Use? Comparison of Means Measures of DispersionConclusionExercises13. Analyzing Survey ScalesOverviewHandling Exits and the Middle of a Five-Point ScaleSetting Benchmarks and Extreme AnalysisHandling the Middle Category in One-Way Intensity ScalesShould Means Be Used with Nominal and Ordinal Scales?The Analytical Tool: Cross TabulationsConclusionExercises14. Data Analysis: Exploring RelationshipsOverviewUsing Crosstabs to Examine RelationshipsControlling for a Third VariableExploring Relationships: Comparison of Means and MediansMeasures of AssociationFrequently Used Measures of AssociationWorking with Interval or Ratio DataConclusionExercises15. Data Analysis: RegressionOverviewBivariate Regression: Key ElementsUsing Bivariate Regression Analysis: Sunshine and TourismMultiple Regression Beta Weights: Relative Predictive Strength Regression in the NewsWhy Did the Violent Crime Rate Drop After 1991?ConclusionExercises16. Data Analysis Using Inferential StatisticsOverviewStatistical Significance: Basic ConceptsThe Logic of Statistical Significance TestingErrors in Tests for Statistical SignificanceCommon Tests for Statistical Significance Chi-Square t-Tests: Analyzing Difference in Means Analysis of Variance Tests for Statistical Significance in Regression AnalysisReporting Results of Statistical SignificancePopulation Estimates and Confidence IntervalsConclusionExercises17. Communicating Research ResultsOverviewEffectively Reporting ResultsReporting DataGeneral Guide for Communicating Research ResultsGuide for Writing an Executive SummaryGuide for Writing a Formal ReportGuide for Using Charts and TablesGuide for Oral PresentationsPresenting Unwelcome InformationMaking Sense of Research ResultsConclusionExercises18. Conclusion: Research at the Intersection of Politics and AdministrationOverviewThe Research Process Revisited Planning Doing Reporting Ethics and Social JusticeManaging Research ProjectsAssessing CredibilityThe Limitations of ScienceThe Intersection of Research, Politics, and AdministrationClosing ObservationsExercisesAppendix A. Mathematical Formulas for Selected StatisticsAppendix B. Statistics as a Second LanguageAppendix C. BibliographyAppendix D. Logic Model TemplateAppendix E. The Generic Design MatrixIndexAbout the Author

Gail Johnson has worked in several public agencies, including the U.S. Government Accountability Office and the U.S. Department of Health and Human Services. Her work with GAO included reports about management of federal agencies, transforming the civil service, and drug use among youth. She has taught in MPA programs for more than fifteen years, worked as consultant with several local governments, and helped design several research workshops for The World Bank. She recently published Trailblazing Governors: Six Remarkable Women, which tells the stories of six of the first generation of women governors. She maintains a blog, Research Demystified, which explores social science research in the context of politics, policy, public administration, program evaluation, and measuring for results and advocacy.