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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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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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