Handbook of Statistics: Epidemiology and Medical Statistics

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Edited by C.R. Rao, J. Philip Miller, and D.C. Rao

Objective of the New Volume: This volume is addressed to statisticians working in biomedical and epidemiological fields who use statistical and quantitative methods in their work. Keeping the applied statisticians in mind, its emphasis is on applications-oriented techniques.

Broad topics to be covered include (among others):

  • Clinical Trials & Study Designs
  • Odds Ratio & Risk Ratio Methods
  • Regression Type Methods
  • Meta-analysis

Target Audience includes:

  • Pharmaceutical companies (theoretical & applied statisticians)
  • Statisticians in FDA, EPA, etc
  • Libraries

Chapters:

  1. Statistical Methods and Challenges in Epidemiology and Biomedical Research. Ross Prentice
  2. Statistical Inference for Causal Effects, with Emphasis on Applications in Epidemiology and Medical Statistics. Donald Rubin
  3. Epidemiological Study Designs. Kenneth Rothman, Sander Greenland, Timothy Lash
  4. Statistical Methods for Assessing Biomarkers and Analyzing Biomarker Data. Stephen Looney and Joseph Hagan
  5. Linear and Nonlinear Regression Methods in Epidemiology and Biostatistics. Charles McCulloch, David Glidden, Stephen Shiboski, Eric Vittinghoff
  6. Logistic Regression. Ed Spitznagel
  7. Count Response Regression Models. Joseph Hilbe and William Greene
  8. Mixed Models. Matthew Gurka and Lloyd Edwards
  9. Survival Analysis. John Klein and Meijie Zhang
  10. A Review of Statistical Analysis for Competing Risks. Melvin Moeschberger, Kevin Tordoff, Nidhi Kochar
  11. Cluster Analysis. Bill Shannon
  12. Factor Analysis and Related Methods. Carol Woods and Michael Edwards
  13. Structural Equations Modeling. Kentaro Hayashi, Peter Bentler, Ke-Hai Yuan
  14. Statistical Modeling in Biomedical Research: Longitudinal Data Analysis. Chengjie Xiong, Kejun Zhu, Kai Yu, Phil Miller
  15. Design and Analysis of Cross-Over Trials. Michael Kenward and Byron Jones
  16. Sequential and Group Sequential Designs in Clinical Trials: Guidelines for Practitioners. Madhu Mazumdar and Heejung Bang
  17. Early Phase Clinical Trials: Phase I and II. Feng Gao, Kim Trinkaus, Phil Miller
  18. Definitive Phase III and Phase IV Clinical Trials. Barry Davis and Sarah Baraniuk
  19. Incomplete Data in Epidemiology and Medical Statistics. Susanne Rassler, Donald Rubin, Elizabeth Zell
  20. Meta-Analysis. Ed Spitznagel
  21. The Multiple Comparison Issue in Health Care Research. Lemuel Moye
  22. Power: Establishing the Optimum Sample Size. Richard Zeller and Yan Yan
  23. Statistical Learning in Medical Data Analysis. Grace Wahba
  24. Evidence-Based Medicine and Medical Decision Making. Dan Mayer
  25. Estimation of Marginal Regression Models with Multiple Source Predictors. Heather Litman, Nicholas Horton, Bernardo Hernandez, Nan Laird
  26. Difference Equations with Public Health Applications. Asha Kapadia and Lemuel Moye
  27. The Bayesian Approach to Experimental Data Analysis. Bruno Lecoutre

Published by Elsevier [1] in 2008.

You can order from this book from Amazon [2]

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