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February 23, 2009178 citations

Statistical Modeling for Biomedical Researchers: A Simple Introduction to the Analysis of Complex Data

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WDWilliam D. Dupont

Key Points

  • The aim is to guide biomedical researchers in selecting and applying advanced statistical techniques.
  • Uses Stata statistical software version 10 for data analysis.
  • Covers linear, logistic, Poisson regression, survival analysis, and various forms of ANOVA.
  • Includes real data sets and an appendix for method selection.
  • Introduces methods in simplest form before extending to more complex scenarios.
  • Helps users grasp complex data analysis without requiring advanced mathematics.

Abstract

The second edition of this standard text guides biomedical researchers 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 again used to perform the analyses, this time employing the much improved version 10 with its intuitive point and click as well as character-based commands. 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 at http://biostat.mc.vanderbilt.edu/dupontwd/wddtext/

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Cite This Study

William D. Dupont (2009) studied this question.

synapsesocial.com/papers/6a61dc606e9a4038e37d8fdbhttps://doi.org/10.1017/cbo9780511575884
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