소장자료
Statistical analysis of medical data using SAS
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- 자료유형
- 단행본
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- 서명/저자사항
- Statistical analysis of medical data using SAS /Geoff Der, Brian S. Everitt.
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- 발행사항
- Boca Raton, FL :Chapman & Hall/CRC,2006.
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- 형태사항
- 428 p. :ill. ;25 cm.
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- 서지주기
- Includes bibliographical references (p. 411-415) and index.
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- 내용주기
- 1. An introduction to SAS - 2. Describing and summarizing data - 3. Basic inference - 4. Scatterplots, correlation, simple regression, and smoothing - 5. Analysis of variance and covariance - 6. Multiple regression - 7. Logistic regression - 8. The generalized linear model - 9. Generalized additive models - 10. Nonlinear regression models - 11. The analysis of longitudinal data I - 12. The analysis of longitudinal data II: models for normal response variables - 13. The analysis of longitudinal data III: non-normal responses - 14. Survival analysis - 15. Analysing multivariate data: principle components and cluster analysis.
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- ISBN
- 158488469X (alk. paper)
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- 언어
- 영어
소장사항
번호 | 소장처 | 청구기호 (권) | 도서상태 | 반납예정일 | 신청/예약 |
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1 | 연세의학도서관/3층 구관/15서가 4열 | 610.285 D427s | 대출가능 | - |
목차
1. An introduction to SAS
2. Describing and summarizing data
3. Basic inference
4. Scatterplots, correlation, simple regression, and smoothing
5. Analysis of variance and covariance
6. Multiple regression
7. Logistic regression
8. The generalized linear model
9. Generalized additive models
10. Nonlinear regression models
11. The analysis of longitudinal data I
12. The analysis of longitudinal data II: models for normal response variables
13. The analysis of longitudinal data III: non-normal responses
14. Survival analysis
15. Analysing multivariate data: principle components and cluster analysis
2. Describing and summarizing data
3. Basic inference
4. Scatterplots, correlation, simple regression, and smoothing
5. Analysis of variance and covariance
6. Multiple regression
7. Logistic regression
8. The generalized linear model
9. Generalized additive models
10. Nonlinear regression models
11. The analysis of longitudinal data I
12. The analysis of longitudinal data II: models for normal response variables
13. The analysis of longitudinal data III: non-normal responses
14. Survival analysis
15. Analysing multivariate data: principle components and cluster analysis