Research Methods: The Essential Knowledge Base / Edition 2 available in Paperback
From an expert team in the research methods field, RESEARCH METHODS: THE ESSENTIAL KNOWLEDGE BASE, 2nd Edition, is written specifically for users who are new to research methods. The book streamlines and clarifies explanations of fundamental, yet difficult, concepts in a familiar, engaging style. Readers learn about the relationship between theory and practice, which helps them become better researchers and better consumers of research.
About the Author
William M. Trochim (Ph.D., Northwestern University) is a Professor in the Department of Policy Analysis and Management at Cornell University and a Professor of Public Health in the Department of Healthcare Policy and Research at the Weill Cornell Medical College (WCMC). He is the Director of the Cornell Office for Research on Evaluation and Director of Evaluation for Extension and Outreach at Cornell, and the Director of Evaluation for the WCMC's Clinical and Translational Science Center. He has taught both undergraduate and graduate required courses in applied social research methods since joining the faculty at Cornell in 1980. Trochim's research interests include the theory and practice of research, conceptualization methods, strategic and operational planning methods, performance management and measurement, and change management. His current research is primarily in the areas of translational research, research-practice integration, evidence-based practice, and evaluation policy.
James P. Donnelly, SUNY-Buffalo Dr. Donnelly is an assistant professor in the Department of Counseling, School and Educational Psychology at the University at Buffalo. He completed his undergraduate degree at Allegheny College, his masters at Claremont Graduate University and his doctorate at the University at Buffalo. He teaches courses related to research methods and health psychology at the graduate level. Previously a psychologist at Roswell Park Cancer Institute, his research and clinical interests are in quality of life issues related to chronic and life limiting illness. He is also affiliated with the Center for Hospice and Palliative Care in Buffalo. He lives in Clarence, New York with his wife Kerry and sons Seamus and Paddy.
Table of Contents
Part I: FOUNDATIONS. 1. Introduction. The Research Enterprise: What Is Research? Translational Research. Research Syntheses and Guidelines. Evidence-Based Practice. An Evolutionary Perspective on the Research Enterprise. Conceptualizing Research: Where Research Topics Come From. The Literature Review. Feasibility Issues. The Language of Research: Research Vocabulary. Types of Studies. Time in Research. Types of Relationships. Hypotheses. Variables. Types of Data. The Unit of Analysis. Deduction and Induction. The Structure of Research: Components of a Research Study. The Validity of Research. 2. Ethics. Foundations of Ethics in Research. Historical Cases of Unethical Research: Nazi Experimentation during WWII and the Nuremberg Code. Stanley Milgram's Obedience Studies. The Thalidomide Tragedy. The Tuskegee Syphilis Study. Evolution of a Modern System of Research Ethics: The Belmont Report. Related Guidelines on Human Subject Participation. Institutional Review Boards (IRBs). Ethics in Clinical Research: Patient Protection versus Access. Ethics in Research with Animals. Ethics in the Production and Publication of Scholarly Work: Honesty in Reporting. Conflict of Interest. Fairness in Publication Credit. 3. Qualitative Approaches to Research. Foundations of Qualitative Research. The Context for Qualitative Research: Generating New Theories or Hypotheses. Developing Detailed Stories to Describe a Phenomenon. Achieving Deeper Understanding of the Phenomenon. Improving the Quality of Quantitative Measures. Qualitative Traditions: Ethnography. Phenomenology. Field Research. Grounded Theory. Qualitative Methods: Participant Observation. Direct Observation. Unstructured Interviewing. Case Studies. Focus Groups. Unobtrusive Methods in Qualitative Research. Qualitative Data: How Different are Quantitative and Qualitative Data? Assessing Qualitative Research: Credibility. Transferability. Dependability. Confirmability. Part II: SAMPLING. 4. Sampling. Foundations of Sampling. Sampling Terminology. External Validity: Two Major Approaches to External Validity in Sampling. Sampling Methods. Nonprobability Sampling: Accidental, Haphazard, or Convenience Sampling. Purposive Sampling. Modal Instance Sampling. Expert Sampling. Quota Sampling. Heterogeneity Sampling. Snowball Sampling. Summary of Nonprobability Methods. Probability Sampling: Theory: The Sampling Distribution. Sampling Error. The Normal Curve in Sampling. Probability Sampling: Procedures: Initial Definitions. Simple Random Sampling. Stratified Random Sampling. Systematic Random Sampling. Cluster (Area) Random Sampling. Multistage Sampling. How Big Should the Sample Be? Summary of Probabilistic Sampling. Threats to External Validity. Improving External Validity. Part III: MEASUREMENT. 5. Introduction to Measurement. Foundations of Measurement. Levels of Measurement. Quality of Measurement. Reliability. Theory of Reliability. Types of Reliability. Validity. Construct Validity and Other Measurement Validity Labels. Threats to Construct Validity. The Social Threats to Construct Validity. Integrating Reliability and Validity. 6. Scales, Tests, and Indexes. Foundations of Scales, Tests, and Indexes. Scales and Scaling. General Issues in Scaling. Purposes of Scaling. Dimensionality. Unidimensional or Multidimensional? Tests. Validity, Reliability and Test Construction. Standardized Tests. Test Fairness. How to Find a Good Test. Indexes. Some Common Indexes. Constructing an Index. 7. Survey Research. Foundations of Survey Research. Types of Survey Research. Questionnaires. Interviews. Selecting the Survey Method. Population Issues. Sampling Issues. Question Issues. Content Issues. Bias Issues. Administrative Issues. Survey Design. Types of Questions. Question Content. Response Format. Question Wording. Question Placement. The Golden Rule. Interviews. The Role of the Interviewer. Training the Interviewers. The Interviewer's Kit. Conducting the Interview. Obtaining Adequate Responses-The Probe. Recording the Response. Concluding the Interview. Part IV: DESIGN. 8. Introduction to Design. Foundations of Design. Research Design and Causality. Establishing Cause and Effect in Research Design. Internal Validity. Developing a Research Design. Types of Designs. Expanding on Basic Designs. 9. Experimental Design. Foundations of Experimental Design. Introduction: The Origins of Experimental Design. Distinguishing Features of Experimental Design. Experimental Design and Threats to Internal Validity. Design Notation for a Two-Group Experimental Design. Difference between Random Selection and Assignment. Classifying Experimental Designs. Signal Enhancing Designs: Factorial Designs. The Basic 2 x 2 Factorial Design. Benefits and Limitations of Factorial Designs. Factorial Design Variations. Noise-Reducing Designs: Randomized Block Designs. Noise-Reducing Designs: Covariance Designs. Hybrid Designs: Switching Replication Experimental Designs. Limitations of Experimental Design. 10. Quasi-Experimental Design. Foundations of Quasi-Experimental Design. The Nonequivalent-Groups Design. Reaching Cause-and-Effect Conclusions with the NEGD. The Regression-Discontinuity Design. The Basic RD Design. The Role of the Comparison Group in RD Designs. The Internal Validity of the RD Design. Statistical Power and the RD Design. Ethics and the RD Design. Other Quasi-Experimental Designs: The Proxy Pretest Design. The Separate Pre-Post Samples Design. The Double-Pretest Design. The Switching-Replications Design. The Nonequivalent Dependent Variables (NEDV) Design. The Regression Point Displacement (RPD) Design. Part V: ANALYSIS AND REPORTING. 11. Introduction to Data Analysis: Foundations of Data Analysis. Conclusion Validity. Threats to Conclusion Validity. Data Preparation: Logging the Data. Checking the Data for Accuracy. Developing a Database Structure. Entering the Data into the Computer. Data Transformations. Descriptive Statistics: The Distribution. Central Tendency. Dispersion or Variability. Correlation. 12. Inferential Analysis. Foundations of Analysis for Research Design. Inferential Statistics. General Linear Model: The Two-Variable Linear Model. The 'General' in the General Linear Model. Dummy Variables. The t-Test. Experimental Analysis: The Two-Group Posttest-Only Randomized Experiment. Factorial Design Analysis. Randomized Block Analysis. Analysis of Covariance. Quasi-Experimental Analysis: Nonequivalent Groups Analysis. Regression-Discontinuity Analysis. Regression Point Displacement Analysis. 13. Communicating Research. Research Communication: Research Communication and the Research-Practice Continuum. General Considerations for Research Communication. The Written Report: Key Elements and Formatting of a Research Paper. Other Forms of Research Communication. Appendix.