Richard D. Hartley is professor in the Department of Criminology & Criminal Justice at University of Texas at San Antonio.Lee Ellis is semi-retired after over thirty years as professor of sociology at Minot State University.Anthony Walsh is professor emeritus of criminal justice at Boise State University.The authors have varied and extensive experience with research methods in criminology and criminal justice as well as in sociology and corollary social/behavioral sciences. All authors have doctoral degrees in Criminology or Criminal Justice, and all have taught research methods courses for criminology and criminal justice as well as sociology. The authors have published in a variety of academic journals from various disciplines and all have published books in the past.

Using an excellent blend of methods, statistics, and theory, the Ellis, Hartley, and Walsh research methods book is a remarkable text that will definitely be valuable to beginning and advanced researchers. I applaud them for their ability to successfully apply research methods to real-world problems, while at the same time use research examples from a vast array of academic disciplines and topics worldwide. Their book should certainly be one that research methods instructors should consider adopting so that students have an all-encompassing methods experience!

• Chapter 1 – The Scientific Method and Criminology and Criminal Justice as Social SciencesLearning to Become a ResearcherCircumscribing Criminology and Criminal JusticeCircumscribing the Social SciencesThe Near Social SciencesOther Disciplines that Utilize Social Science Research MethodsTwo Special Disciplines Linked to Social ScienceFeatures of the Scientific MethodThe Scientific SpiritTypes of Issues Addressed by Social ScientistsSummaryChapter 2 – Formulating Scientific Questions and Locating Background ResearchThe Nature of Scientific VariablesConceptual Versus Operational Definitions of VariablesLevels of MeasurementFormulating and Refining Scientific QuestionsLocating Information on Topics of InterestDistinctiveness of Scientific CommunicationHow Scientific Research Gets Reviewed and Sometimes PublishedSummaryChapter 3 – Ethical Issues in the Social SciencesResponsibilities to Participants of ResearchDeceiving or Causing Harm to Human ParticipantsObtaining Institutional Approval for Conducting ResearchResponsibilities to Fellow Social and Behavioral ScientistsEthics in Criminology and Criminal Justice ResearchResponsibilities to HumanitySummaryChapter 4 – Theories, Models, Hypotheses, and Empirical RealityThe Concept of CausationThe Nature of Scientific TheorizingAssessing the Merit of a TheoryThe Role of Theory in the Research ProcessScientific Models, Laws, and ParadigmsHypothesis Testing and Attempts to GeneralizeThe Null Hypothesis and Type I and Type II ErrorsSummaryChapter 5 – The Concepts of Reliability, Validity, and Precision in MeasurementUsing the Concept of Correlation to Discuss Measurement AccuracyThree Elements of Accurate MeasurementReliabilityValidityPrecisionUsing Factor Analysis to Refine Measurement AccuracySome Closing Remarks about Reliability, Validity, and PrecisionSummaryChapter 6 – Surveying and Sampling The Nature of Scientific SurveysBasic TerminologyRepresentative Versus Non-representative SamplesProbability Versus Non-Probability Sampling MethodsSample SizeSurveying Over TimeServing as a Respondent to a Research QuestionnairesAssessing Sample Attrition, its Extent and Causes Computer-Assisted InterviewingLimiting Sample AttritionInaccuracies in Self-ReportsTechniques for Minimizing and Detecting DishonestySummaryChapter 7 – Measuring Crime and CriminalityMeasuring Crime and Criminal BehaviorThe Uniform Crime Reports: Counting Crime OfficiallyNIBRS: The “New and Improved” UCRCrime Victimization Survey DataSelf-Reported Crime SurveysMeasuring Criminal Propensity: Moving from Crime to CriminalitySummaryChapter 8 – Controlled ExperimentationBasic Experimental TerminologyMain Types of Experimental DesignsPitfalls with Human ExperimentationShortcomings of Experimental ResearchSummaryChapter 9 – Quasi-ExperimentationQuasi-Experiments Compared to Controlled ExperimentsQuasi-Experimental Designs in the Narrower SenseQuasi-Experimental Designs in the Broader SenseQuasi-Experimental Designs for Addressing Nature-Nurture IssuesSummaryChapter 10 – Data Based on Self-Reports: Guidelines for Constructing QuestionnairesBasic TerminologyAdvantages and Disadvantages of Data Based on Self-ReportsResponse Options for QuestionsDeciding Which Response Options to UseTypes of Self-Reported ItemsGuidelines for Item ConstructionTypes of Questions to AvoidCombining Two or More Items to Improve ReliabilityTime Diaries: A Special Type of QuestionnaireComputerized Questionnaires and Use of the InternetFinal Comments on Questionnaire DataSummaryChapter 11 – Direct Observations: Qualitative and Quantitative DataQualitative Direct ObservationsParticipant ObservationsEthnographic ObservationsCase StudiesFocus Group ResearchArchaeological DataProcedures in Ethnographic/Participant Observation Data CollectionQuantitative Direct ObservationsLaboratory/Clinical ObservationsField ResearchDirect Observations among Non-Human AnimalsContent AnalysisClosing Comments on Direct ObservationSummaryChapter 12 – Archival Data Analysis, Meta-Analysis, and Evaluation Research Units of AnalysisArchival DataAnalyzing Cross-Cultural AtlasesReview Articles and Meta-AnalysesConceptualizing Evaluation ResearchProcess and Impact Evaluation ResearchHistory of Evaluation ResearchLocating Reports of Evaluation ResearchProgram Evaluation: Doing it RightSummaryChapter 13 – Univariate Statistics and the Concept of Statistical SignificanceThe Nature of Univariate Statistical ConceptsMeasures of Central TendencyMeasures of DispersionIllustrating the Concepts of Averages and DispersionsBuilding the Concept of Statistical SignificanceHypothesis Testing and the Concept of the Null HypothesisInferential StatisticsClosing Remarks About Statistical Significance and Inferential StatisticsSummaryChapter 14 – Bi/Multivariate Statistics: The Concept of CorrelationBackground for Bivariate StatisticsConstructing ScattergramsCurvilenear Versus Linear CorrelationsInterpreting Statements about the Strength of CorrelationsVariability and CorrelationsThe Statistical Significance of Correlation Coefficients Interpreting Two Studies Based on Correlation Reflections on the Importance of Statistics in the Research ProcessMultivariate Statistics: When Bivariate Statistics Are Not EnoughClosing Comments on Multivariate Statistics Summary