Research Methods for the Behavioral Sciences

Gregory J. Privitera is a three-time national-award-winning author and a professor of psychology at St. Bonaventure University where he is a recipient of its highest teaching honor, The Award for Professional Excellence in Teaching, and its highest honor for scholarship, The Award for Professional Excellence in Research and Publication. Dr. Privitera received his PhD in behavioral neuroscience in the field of psychology at the State University of New York at Buffalo and continued with his postdoctoral research at Arizona State University. His texts span diverse topics in psychology and the behavioral sciences and include an introductory psychology text, three statistics texts, two research methods texts, and multiple other texts bridging knowledge creation across health, health care, and analytics. In addition, Dr. Privitera has authored more than three dozen peer-reviewed papers aimed at advancing our understanding of health, health literacy, and informing policy in health care. His research has earned recognition by the American Psychological Association and in media to include Oprah’s Magazine, Time Magazine and the Wall Street Journal. He mentors a variety of undergraduate research projects at St. Bonaventure University, where dozens of students, many of whom have gone on to earn graduate and doctoral degrees at various institutions, have coauthored and presented research work. In addition to his teaching, research, and advisement, Dr. Privitera is a veteran of the U.S. Marine Corps, is an identical twin, and is married with two daughters, Grace Ann and Charlotte Jane, and two sons, Aiden Andrew and Luca James.

Privitera′s book is the best book I′ve seen for my audience, and it is priced well below what some of the lesser-quality competitors offer. It is accessible to the non-math major and is written in a very good style and tone for the typical behavioral science student.

• About the AuthorAcknowledgmentsPrefaceTo the Student—How to Use SPSS With This BookSection I • Scientific InquiryChapter 1 • Introduction to Scientific ThinkingScience as a Method of KnowingThe Scientific MethodOther Methods of KnowingThe Goals of ScienceApproaches in Acquiring KnowledgeDistinguishing Science From PseudoscienceChapter 2 • Generating Testable IdeasGenerating Interesting and Novel IdeasConverting Ideas to Hypotheses and TheoriesDeveloping Your Idea: Deduction and InductionPerforming a Literature ReviewThe “3 Cs” of an Effective Literature ReviewTesting Your Idea: Confirmation and DisconfirmationChapter 3 • Research EthicsEthics in Behavioral ResearchThe Need for Ethics Committees in Research: A Historical SynopsisEthics: Examples From PsychologyHuman Participant Research: IRBs and the APA Code of ConductAnimal Subject Research: IACUCs and the APA Code of ConductAdditional Ethical Considerations: Scientific IntegritySection II • Defining and Measuring Variables, Selecting Samples, and Choosing an Appropriate Research DesignChapter 4 • Identifying Scientific VariablesCriteria for Defining and Measuring VariablesConstructs and Operational DefinitionsTypes of VariablesScales of MeasurementReliability of a MeasurementValidity of a MeasurementSelecting a Measurement ProcedureSPSS in Focus: Entering and Coding DataChapter 5 • Sampling From PopulationsSelecting Samples From PopulationsMethods of Sampling: Nonprobability SamplingMethods of Sampling: Probability SamplingSampling Error and Standard Error of the MeanPotential Biases in SamplingSPSS in FocusChapter 6 • Choosing a Research DesignDesigning a Study to Answer a QuestionCategories of Research DesignInternal and External ValidityDemonstrating Cause in an ExperimentThreats to the Internal Validity of a Research StudyThreats to the External Validity of a Research StudyExternal Validity, Experimentation, and RealismSection III • Nonexperimental Research DesignsChapter 7 • Qualitative Research DesignsAn Overview of Qualitative ResearchRole of the Researcher and Entry Into the FieldSampling in Qualitative ResearchTypes of Qualitative DataQualitative Research Designs: Phenomenology, Ethnography, and Case StudyChapter 8 • Naturalistic and Existing Data Research DesignsAn Overview of Naturalistic ObservationTechniques for Conducting Naturalistic ObservationsAn Overview of Existing Data DesignsExisting Data Research Designs: Archival Research, Content Analysis, and Meta-AnalysisChapter 9 • Survey and Correlational Research DesignsAn Overview of Survey DesignsRules for Writing Survey ItemsAdministering SurveysSurveys, Sampling, and Nonresponse BiasThe Structure of Correlational DesignsDescribing the Relationship Between VariablesLimitations in InterpretationCorrelation, Regression, and PredictionSPSS in Focus: Correlation and Linear RegressionSection IV • Quasi-Experimental and Experimental Research DesignsChapter 10 • Quasi-Experimental and Single-Case Experimental DesignsAn Overview of Quasi-Experimental DesignsQuasi-Experimental Design: Nonequivalent Control Group DesignsQuasi-Experimental Design: Time Series DesignsQuasi-Experimental Design: Developmental DesignsAn Overview of Single-Case Experimental DesignsSingle-Case Baseline-Phase DesignsValidity, Stability, Magnitude, and GeneralityChapter 11 • Between-Subjects Experimental DesignsConducting Experiments: Between-Subjects DesignManipulation and the Independent VariableVariability and the Independent VariableComparing Two Independent SamplesSPSS in Focus: Two-Independent-Sample t TestComparing More Than Two Independent SamplesSPSS in Focus: One-Way Between-Subjects ANOVAMeasuring the Dependent VariableChapter 12 • Within-Subjects Experimental DesignsConducting Experiments: Within-Subjects DesignControlling Time-Related FactorsIndividual Differences and VariabilityComparing Two Related SamplesSPSS in Focus: Related-Samples t TestComparing Two or More Related SamplesSPSS in Focus: One-Way Within-Subjects ANOVAAn Alternative to Pre-Post Designs: Solomon Four-Group DesignComparing Between-Subjects and Within-Subjects DesignsChapter 13 • Factorial Experimental DesignsTesting Multiple Factors in the Same ExperimentTypes of Factorial DesignsMain Effects and InteractionsIdentifying Main Effects and Interactions in a GraphIncluding Quasi-Independent Factors in an ExperimentReasons for Including Two or More Factors in an ExperimentSPSS in Focus: Computing a Factorial ANOVASection V • Analyzing, Interpreting, And Communicating Research DataChapter 14 • Analysis and Interpretation: Exposition of DataDescriptive Statistics: Why Summarize Data?Frequency Distributions: Tables and GraphsMeasures of Central TendencyMeasures of VariabilitySPSS in Focus: Central Tendency and VariabilityGraphing Means and CorrelationsUsing Correlation to Describe ReliabilitySPSS in Focus: Cronbach’s Alpha and Cohen’s KappaChapter 15 • Analysis and Interpretation: Making Decisions About DataInferential Statistics: What Are We Making Inferences About?Types of Error and PowerParametric Tests: Applying the Decision TreeNonparametric Tests: Applying the Decision TreeSPSS in Focus: The Chi-Square TestsEffect Size: How Big Is an Effect in the Population?Estimation: What Are the Possible Values of a Parameter?Chapter 16 • Communicating Research: Preparing Manuscripts, Posters, and TalksElements of CommunicationWriting a Manuscript: Writing Style and LanguageElements of an APA-Style ManuscriptPresenting a PosterAppendix A: APA-Style Writing, Sample Manuscript, and PostersAppendix B: Instructions for Randomizing and CounterbalancingAppendix C: SPSS General Instructions Guide and Statistical TablesGlossaryReferencesIndex