TY  - BOOK
AU  - Ambrosius,Walter T.
TI  - Topics in biostatistics
T2  - Methods in molecular biology
SN  - 9788184894271
U1  - 000SB:570 23
PY  - 2010///
CY  - New Delhi
PB  - Humana Press
KW  - Biometry
KW  - Methodology.
KW  - methods.
KW  - Informatics
N1  - Includes index; 1. Study design: the basics / Hyun Ja Lim and Raymond G. Hoffmann --
2. Observational study design / Raymond G. Hoffmann and Hyun Ja Lim --
3. Descriptive statistics / Todd G. Nick --
4. Basic principles of statistical inference / Wanzhu Tu --
5. Statistical inference on categorical variables / Susan M. Perkins --
6. Development and evaluation of classifiers / Todd A. Alonzo and Margaret Sullivan Pepe --
7. Comparison of means / Nancy Berman --
8. Correlation and simple linear regression / Lynn E. Eberly --
9. Multiple linear regression / Lynn E. Eberly --
10. General linear models / Edward H. Ip --
11. Linear mixed effects models / Ann L. Oberg and Douglas W. Mahoney --
12. Design and analysis of experiments / Jonathan J. Shuster --
13. Analysis of change / James J. Grady --
14. Logistic regression / Todd G. Nick and Kathleen M. Campbell --
15. Survival analysis / Hongyu Jiang and Jason P. Fine --
16. Basic Bayesian methods / Mark E. Glickman and David A. van Dyk --
17. Overview of missing data techniques / Ralph B. D'agostino, Jr. --
18. Statistical topics in the laboratory sciences / Curtis A. Parvin --
19. Power and sample size / L. Douglas Case and Walter T. Ambrosius --
20. Microarray analysis / Grier P. Page [and others] --
21. Association methods in human genetics / Carl D. Langefeld and Tasha E. Fingerlin --
22. Genome mapping statistics and bioinformatics / Josyf C. Mychaleckyj --
23. Working with a statistician / Nancy Berman and Christina Gullion--
Index
N2  - Presents a multidisciplinary survey of biostatics methods, each illustrated with hands-on examples. Methods range from the elementary, including descriptive statistics, study design, statistical interference, categorical variables, evaluation of diagnostic tests, comparison of means, linear regression, and logistic regression. These introductory methods create a portfolio of biostatistical techniques for both novice and expert researchers. More complicated statistical methods are introduced as well, including those requiring either collaboration with a biostatistician or the use of a statistical package. Specific topics of interest include microarray analysis, missing data techniques, power and sample size, statistical methods in genetics.
ER  -