Statistical Modeling for Biomedical Researchers: A Simple Introduction to the Analysis of Complex Data
Cambridge University Press, Feb 12, 2009 - Medical - 522 pages
For biomedical researchers, the new edition of this standard text guides readers in the selection and use of advanced statistical methods and the presentation of results to clinical colleagues. It assumes no knowledge of mathematics beyond high school level and is accessible to anyone with an introductory background in statistics. The Stata statistical software package is used to perform the analyses, in this edition employing the intuitive version 10.
Topics covered include linear, logistic and Poisson regression, survival analysis, fixed-effects analysis of variance, and repeated-measure analysis of variance. Restricted cubic splines are used to model non-linear relationships. Each method is introduced in its simplest form and then extended to cover more complex situations. An appendix will help the reader select the most appropriate statistical methods for their data. The text makes extensive use of real data sets available online through Vanderbilt University.
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Probability density function
Simple linear regression
Multiple linear regression
Simple logistic regression
Multiple logistic regression
covariates on the response variable
Introduction to survival analysis
Multiple Poisson regression
IO Fixed effects analysis of variance
A Summary of statistical models discussed
B Summary of Stata commands used in this text
Hazard regression analysis
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Statistical Modeling for Biomedical Researchers: A Simple Introduction to ...
William D. Dupont
No preview available - 2009
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