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Topics in biostatistics / edited by Walter T. Ambrosius.

Contributor(s): Material type: TextTextSeries: Publication details: Totowa, N.J. : Humana Press, c2007.Description: xii, 528 p. : illISBN:
  • 9781588295316 (alk. paper)
  • 1588295311 (alk. paper)
Subject(s): DDC classification:
  • 574.0212 TOP
Online resources:
Contents:
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.
Summary: 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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Holdings
Item type Current library Home library Call number Status Date due Barcode
Book Book Dept. of Biochemistry Processing Center Dept. of Biochemistry 570.15195 TOP (Browse shelf(Opens below)) Available BCH3511

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.

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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