| Description |
xii, 596 pages : illustrations ; 26 cm |
| Contents |
1. The new stats: Attitudes for the twenty-first century -- PART I: BEST PRACTICES IN MEASUREMENT -- 2. Setting standards and establishing cut scores on criterion-referenced assessments: Some technical and practical considerations -- 3. Best practices in interrater reliability: three common approaches -- 4. An introduction to Rasch Measurement -- 5. Applications of the Multifaceted Rasch Model -- 6. Best Practices in Exploratory Factor Analysis -- PART II: SELECTED BEST PRACTICES IN RESEARCH DESIGN -- 7. Replication statistics -- 8. Mixed Methods research in the social sciences -- 9. Designing a Rigorous Small Sample Study -- 10. Replicated field study design -- 11. Best practices in quasi-experimental designs: matching methods for causal inference -- 12. An introduction to Meta-Analysis -- PART III: BEST PRACTICES IN DATA CLEANING AND THE BASICS OF DATA ANALYSIS -- 13. Best Practices in data transformations: The overlooked effect of minimum values -- 14. Best Practices in data cleaning: How Outliers and "fringeliers" can increase error rates and decrease the quality and precision of your results -- 15. How to deal with missing data: conceptual overview and details for implementing two modern methods -- 16. Is Disattenuation of effects a best practice? -- 17. Computing and interpreting effect sizes, confidence intervals, and confidence intervals for effect sizes -- 18. Robust methods for detecting and describing associations -- PART IV: BEST PRACTICES QUANTITATIVE METHODS -- 19. Resampling: A conceptual and procedural introduction -- 20. Creating Valid Prediction Equations in Multiple Regression: Shrinkage, double cross-validation, and confidence intervals around predictions -- 21. Best practices in analyzing count data: Poisson regression -- 22. Testing the assumption of analysis of variance -- 23. Best practice in the analysis of variance -- 24. Binary Logistic regression -- 25. Bringing balance and technical to reporting odds ratios and the results of logistic regression analyses -- 26. Multinomial logistic regression -- 27. Enhancing Accuracy in Research Using Regression Mixture Analysis -- 28. Mediation, Moderation, and the Study of Individual Differences -- PART V: BEST ADVANCED PRACTICES QUANTITATIVE METHODS -- 29. A brief introduction toHierarchical Linear Modeling -- 30. Best practioces in Analysis of longitudinal data: a multilevel approach -- 31. Analysis of Moderator effects in Meta-Analysis -- 32. Best practices in Structural Equation Modeling -- 33. Introduction to Bayesian modeling for the social sciences -- 34. Using R for Data Analysis: A Best Practice for Research |
| Summary |
Summary: "The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century , identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better."--Publisher description |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Psychology -- Research -- Methodology.
|
|
Quantitative research.
|
|
Social sciences -- Research -- Methodology.
|
|
Social sciences -- Mathematical models.
|
| Author |
Osborne, Jason W.
|
| LC no. |
2007020488 |
| ISBN |
9781412940658 (cloth) |
|
