| 000 | 00000cam u2200205 a 4500 | |
| 001 | 000045939397 | |
| 005 | 20180412133429 | |
| 008 | 180412s2013 enka b 001 0 eng | |
| 010 | ▼a 2012050470 | |
| 020 | ▼a 9781107030039 (hardback) | |
| 020 | ▼a 9781107699922 (paperback) | |
| 035 | ▼a (KERIS)BIB000013319689 | |
| 040 | ▼a 211019 ▼c 211009 ▼d 211009 | |
| 082 | 0 0 | ▼a 614.4/07/27 ▼2 22 |
| 084 | ▼a 614.40727 ▼2 DDCK | |
| 090 | ▼a 614.40727 ▼b T974a2 | |
| 100 | 1 | ▼a Twisk, Jos W. R., ▼d 1962-. |
| 245 | 1 0 | ▼a Applied longitudinal data analysis for epidemiology : ▼b a practical guide / ▼c Jos W.R. Twisk, Department of Epidemiology and Biostatistics, Medical Centre and the Department of Health Sciences of the Vrije Universteit, Amsterdam. |
| 250 | ▼a 2nd ed. | |
| 260 | ▼a Cambridge ; ▼a New York : ▼b Cambridge University Press, ▼c 2013. | |
| 300 | ▼a xiv, 321 p. : ▼b ill. ; ▼c 25 cm. | |
| 490 | 0 | ▼a Cambridge medicine |
| 500 | ▼a Previous edition: 2003. | |
| 504 | ▼a Includes bibliographical references (p. 305-315) and index. | |
| 505 | 8 | ▼a Machine generated contents note: Preface; Acknowledgements; 1. Introduction; 2. Study design; 3. Continuous outcome variables; 4. Continuous outcome variables - relationships with other variables; 5. The modelling of time; 6. Other possibilities for modelling longitudinal data; 7. Dichotomous outcome variables; 8. Categorical and 'count' outcome variables; 9. Analysis data from experimental studies; 10. Missing data in longitudinal studies; 11. Sample size calculations; 12. Software for longitudinal data analysis; 13. One step further; References; Index. |
| 650 | 0 | ▼a Epidemiology ▼x Research ▼x Statistical methods. |
| 650 | 0 | ▼a Epidemiology ▼v Longitudinal studies. |
| 650 | 0 | ▼a Epidemiology ▼x Statistical methods. |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 의학도서관/자료실(3층)/ | 청구기호 614.40727 T974a2 | 등록번호 131052265 (2회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
| No. 2 | 소장처 의학도서관/자료실(3층)/ | 청구기호 614.40727 T974a2 | 등록번호 131052279 (3회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.
A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.
정보제공 :
목차
Preface; Acknowledgements; 1. Introduction; 2. Study design; 3. Continuous outcome variables; 4. Continuous outcome variables - relationships with other variables; 5. The modelling of time; 6. Other possibilities for modelling longitudinal data; 7. Dichotomous outcome variables; 8. Categorical and 'count' outcome variables; 9. Analysis data from experimental studies; 10. Missing data in longitudinal studies; 11. Sample size calculations; 12. Software for longitudinal data analysis; 13. One step further; References; Index.
정보제공 :