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| 현재위치 : 홈 > 도서목록 > 전체도서목록 > 통계 |
| Missing Data in Clinical Studies |
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| 지은이 |
: Molenberghs |
| 발행일 |
: 2007 년 |
| ISBN |
: 9780470849811 |
| 정행가 |
: 49,000 원 |
| 페이지 |
: 504 페이지 |
| 판행수 |
: 1판 |
| 출판사 |
: Wiley |
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| 저자 및 역자 소개 |
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| 차례 |
I Preliminaries
1. Introduction
2. Key Examples
3. Terminology and Framework
II Classical Techniques and the Need for Modelling
4. A Perspective on Simple Methods
5. Analysis of the Orthodontic Growth Data
6. Analysis of the Depression Trials
III Missing at Random and Ignorability
7. The Direct Likelihood Method
8. The Expectation-Maximization Algorithm
9. Multiple Imputation
10. Weighted Estimating Equations
11. Combining GEE and MI
12. Likelihood-Based Frequentist Inference
13. Analysis of the Age-Related Macular Degeneration Trial
14. Incomplete Data and SAS
IV Missing Not at Random
15. Selection Models
16. Pattern-Mixture Models
17. Shared-Parameter Models
18. Protective Estimation
V Sensitivity Analysis
19. MNAR, MAR, and the Nature of Sensitivity
20. Sensitivity Happens
21. Regions of Ignorance and Uncertainty
22. Local and Global Influence Methods
23. The Nature of Local Influence
24. A Latent-Class Mixture Model for Incomplete Longitudinal Gaussian Data
VI Case Studies
25. The Age-Related Macular Degeneration Trial
26. The Vorozole Study
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