Introduction to meta-analysis /
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Main Authors: | |
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Group Author: | ; ; |
Published: |
John Wiley & Sons, Inc.,
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Publisher Address: | Hoboken, NJ : |
Publication Dates: | 2021. |
Literature type: | Book |
Language: | English |
Edition: | Second edition. |
Subjects: | |
Item Description: | Previous edition: 2009. |
Carrier Form: | xxxvi, 500 pages : illustrations ; 27 cm |
Bibliography: | Includes bibliographical references (pages [479]-489) and index. |
ISBN: |
9781119558354 1119558352 |
Index Number: | R853 |
CLC: | R311 |
Call Number: | R311/B731/2nd ed. |
Contents: | Part 1. Introduction: 1. How a meta-analysis works -- 2. Why perform a meta-analysis. -- Part 2. Effect size and precision: 3. Overview -- 4. Effect sizes based on means -- 5. Effect sizes based on binary data (2 × 2 tables) -- 6. Effect sizes based on correlations -- 7. Converting among effect sizes -- 8. Factors that affect precision -- 9. Concluding remarks -- 10. Overview -- 11. Fixed-effect model -- 12. Random-effects model -- 13. Fixed-effect versus random-effects models -- 14. Worked examples (part 1). -- Part 4. Heterogeneity: 15. Overview -- 16. Identifying and quantifying heterogeneity -- 17. Prediction intervals -- 18. Worked examples (part 2) -- 19. An intuitive look at heterogeneity -- 20. Classifying heterogeneity as low, moderate, or high. -- Part 5. Explaining heterogeneity: 21. Subgroup analyses -- 22. Meta-regression -- 23. Notes on subgroup analyses and meta-regression. -- Part 6. Putting it all in context: 24. looking at the whole picture -- 25. Limitations of the random-effects model -- 26. Knapp-Hartung adjustment. -- Part 7. Complex data structures: 27. Overview -- 28. Independent subgroups within a study -- 29. Multiple outcomes or time-points within a study -- 30. Multiple comparisons within a study -- 31. Notes on complex data structures. -- Part 8. Other issues: 32. Overview -- 33. Vote counting--a new name for an old problem -- 34. Power analysis for meta-analysis -- 35. Publication bias. -- Part 9. Issues related to effect size: 36. Overview -- 37. Effect sizes rather than P-values -- 38. Simpson's Paradox -- 39. Generality of the basic inverse-variance method. -- Part 10. Further methods: 40. Overview -- 41. Meta-analysis methods based on direction and P-values -- 42. Further methods for dichotomous data -- 43. Psychometric meta-analysis. -- Part 11. Meta-analysis in context: 44. Overview -- 45. When does it make sense to perform a meta-analysis? -- 46. Reporting the results of a meta-analysis -- 47. Cumulative meta-analysis -- 48. Criticisms of meta-analysis -- 49. Comprehensive meta-analysis software -- 50. How to explain the results of an analysis. -- Part 12. Resources: 51. Software for meta-analysis -- 52. Web sites, societies, journals, and books. |