http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
strategies for description and causation
xxxviii, 650, 14, 18, 7 pages : chiefly color illustrations ; 26 cm.
Authors Dahlia K. Remler and Gregg G. Van Ryzin are back with the third edition of their innovative, standard-setting text, Research Methods in Practice: Strategies for Description and Causation. Imbued with a deep commitment to making social and policy research methods accessible and meaningful, the third edition of this text motivates readers to examine the logic and limits of social science research from academic journals and government reports. A central theme of causation versus description runs through the text, with an emphasis on the idea that causal research is essential to understanding the original of social problems and their potential solutions. Readers will find excitement in the research experience as the best hope for improving the world in which we live, while also acknowledging the trade-offs and uncertainties in real-world research. The new edition of this text has been thoroughly updated to reflect changes in both research and methods. An entirely revamped chapter on secondary data expands to cover big data, including ethics, as well focusing more on the variety and challenges of using public and research data including data on COVID. The chapter on logic models now focuses on examples of community policing to demonstrate effectiveness. Survey coverage now includes a much greater focus on online surveys, with detailed examples of non-response bias using data from the 2016 and 2020 US presidential elections. The open access and open data movements, along with preregistration, now feature prominently in the politics of research.
PART I: FOUNDATIONS -- Chapter 1. Research in the real world -- Learning objectives -- Do methods matter? -- Research, policy, and practice -- Evidence can mislead -- What is research? -- Descriptive and causal research -- Epistemology: ways of knowing -- Approaching research from different angles -- Ethics of research -- Conclusion: the road ahead -- Exercises -- Chapter 2. Theory, models, and research questions -- Learning objectives -- Community policing comes to Portland -- What is a theory? -- What is a model? -- Logic models: mechanisms of programs -- Alternative perspectives on theory in social research -- How to find and focus research questions -- Conclusion: theories are practical -- Chapter 3. Qualitative research -- Learning objectives -- Fighting malaria in Kenya -- What is qualitative research? -- Existing qualitative data -- Qualitative interviews -- Focus groups -- Qualitative observation -- Participant observation and ethnography -- Case study research -- Qualitative data analysis -- The qualitative-quantitative debate -- Ethics in qualitative research -- Conclusion: matching methods to questions -- Exercises -- PART II: STRATEGIES FOR DESCRIPTION -- Chapter 4. Measurement -- Learning objectives -- The U.S. poverty measure -- What is measurement? -- Conceptualization -- Operationalization -- Validity -- Criteron-related validity -- Measurement error -- Reliability -- Validity and reliability in qualitative research -- Levels of measurement -- Measurement in the real world: trade-offs and choices -- Conclusion: measurement matters -- Chapter 5. Sampling -- Learning objectives -- Gauging the fallout from Hurricane Katrina -- Generalizability -- Basic sampling concepts -- Problems and biases in sampling -- Nonprobability sampling -- Random (probability) sampling -- Sampling distributions, standard errors, and confidence intervals -- Sampling in practice -- Sampling and generalizability: a summary -- Exercises -- Chapter 6. Secondary data -- Learning objectives -- Tracking a global pandemic -- Quantitative data forms and structures -- Administrative records -- Aggregate data tables -- Public use microdata -- Secondary qualitative data -- Big data -- Linking data -- Some limitations of secondary data -- Conclusion -- Exercises -- Chapter 7. Surveys and other primary data -- Learning objectives -- Taking the nation's economic pulse -- When should you do a survey? -- Steps in the survey research process -- Modes of survey data collection -- Crafting a questionnaire -- Ethics of survey research -- Other ways to collection primary data -- Conclusion -- Exercises -- PART III: STATISTICAL TOOLS AND INTERPRETATIONS -- Chapter 8. Making sense of the numbers -- Learning objectives -- "Last weekend I walked eight" -- Units, rates, and ratios -- Statistics starting point: variables in a data set -- Distributions -- Measures of center: mean and median -- Measures of spread and variation -- Relationships between categorical variables -- Relationships between quantitative variables: scatterplots and correlation -- Simple regression: best-fit straight line -- Practical significance -- Statistical software -- Conclusion: tools for description and causation -- Exercises -- Chapter 9. Making sense of inferential statistics -- Learning objectives -- But is it significant? -- Statistical inference: what's it good for? -- The sampling distribution: foundation of statistical inference -- Confidence intervals -- Significance tests -- Statistical significance, practical significance, and power -- Issues and extensions of statistical inference -- Conclusion -- Exercises -- Chapter 10. Making sense of multivariate statistics -- Learning objectives -- Multiple regression: the basics -- Inference for regression -- Categorical independent variables -- Interactions in regression -- Functional form and transformations in regression -- Categorical variables as dependent variables in regression -- Which statistical methods can I use? -- Other multivariate methods -- Conclusion -- Exercises -- PART IV: STRATEGIES FOR CAUSATION -- Chapter 11. Causation -- Learning objectives -- Family dinners and teenage substance abuse -- Alternative explanations of a correlation -- Causal mechanisms -- Evidence of causation: some critical clues -- Self-selection and endogeneity -- The counterfactual definition of causation -- Experimentation and exogeneity: making things happen -- Conclusion: tools to probe causation -- Exercises -- Chapter 12. Observational studies -- Learning objectives -- Private versus public schools -- What is an observational study? -- Control variables -- Matching -- Control variables: an empirical example -- How to choose control variables -- Epidemiological approaches to observational studies -- Conclusion: observational studies in perspectives -- Exercises -- Chapter 13. Using regression to estimate causal effects -- Leanring objectives -- Cigarette taxes and smoking -- From stratification to multiple regression -- Does greenery affect birth outcomes -- Further topics in regression for estimating causal effects -- Control variables with exogenous independent variables: the gender earnings gap -- Other multivariate techniques for observational studies -- Conclusion: a widely used strategy, with drawbacks -- Exercises -- Chapter 14. Randomized experiments -- Learning objectives -- Time limits on welfare -- Random assignment: creating statistical equivalence -- The logic of randomized experiments: exogeneity revisited -- The settings of randomized experiments -- Generalizability of randomized experiments -- Variations on the design of experiments -- Artifacts and experiments -- Analysis of randomized experiments -- Ethics of randomized experiments -- Qualitative methods and randomized experiments -- conclusion: a gold standard, with limitations -- Exercises -- Chapter 15. Natural and quasi experiments -- Learning objectives -- A casino benefits the mental health of Cherokee children -- What are natural and quasi experiments? -- Internal validity of natural and quasi experiments -- Generalizability of natural and quasi experiments -- Types of natural and quasi experimental studies -- Difference-in-differences strategy -- Instrumental variables and regression discontinuity -- Regression discontinuity -- Ethics of quasi and natural experiments -- Conclusion -- Exercises -- PART V: CONTEXT AND COMMUNICATION -- Chapter 16. The poltics, production, and ethics of research -- Learning objectives -- Risking your baby's health -- From research to policy -- The production of research -- Making research ethical -- Making research open and transparent -- Conclusion -- Exercises -- Chapter 17. How to find, review, and present research -- Learning objectives -- Where to find research -- How to search for studies -- How to write a literature review -- How to communicate your own research -- How to publish your research -- Conclusion -- Exercises -- Glossary -- References -- Index.
Includes bibliographical references and index.