TY  - BOOK
AU  - Ambrosius,Walter T.
TI  - Topics in biostatistics
T2  - Methods in molecular biology,
SN  - 9781588295316 (alk. paper)
U1  - 574.0212 
PY  - 2007///
CY  - Totowa, N.J.
PB  - Humana Press
KW  - Biometry
KW  - Informatics
KW  - Biostatistik
N1  - Includes bibliographical references and index; Study design: the basics / Hyun Ja Lim and Raymond G. Hoffmann -- Observational study design / Raymond G. Hoffmann and Hyun Ja Lim -- Descriptive statistics / Todd G. Nick -- Basic principles of statistical inference / Wanzhu Tu -- Statistical inference on categorical variables / Susan M. Perkins -- Development and evaluation of classifiers / Todd A. Alonzo and Margaret Sullivan Pepe -- Comparison of means / Nancy Berman -- Correlation and simple linear regression / Lynn E. Eberly -- Multiple linear regression / Lynn E. Eberly -- General linear models / Edward H. Ip -- Linear mixed effects models / Ann L. Oberg and Douglas W. Mahoney -- Design and analysis of experiments / Jonathan J. Shuster -- Analysis of change / James J. Grady -- Logistic regression / Todd G. Nick and Kathleen M. Campbell -- Survival analysis / Hongyu Jiang and Jason P. Fine -- Basic Bayesian methods / Mark E. Glickman and David A. van Dyk -- Overview of missing data techniques / Ralph B. D'agostino, Jr. -- Statistical topics in the laboratory sciences / Curtis A. Parvin -- Power and sample size / L. Douglas Case and Walter T. Ambrosius -- Microarray analysis / Grier P. Page ... [et al.] -- Association methods in human genetics / Carl D. Langefeld and Tasha E. Fingerlin -- Genome mapping statistics and bioinformatics / Josyf C. Mychaleckyj -- Working with a statistician / Nancy Berman and Christina Gullion
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.--
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