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  3. Applied Linear Models with SAS
  • Cited by 7
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    • Publisher:
      Cambridge University Press
      Publication date:
      June 2012
      May 2010
      ISBN:
      9780511778643
      9780521761598
      DOI:
      https://doi.org/10.1017/CBO9780511778643
      Dimensions:
      (253 x 215 mm)
      Weight & Pages:
      0.67kg, 288 Pages
      Dimensions:
      Weight & Pages:
      • Subjects:
      Statistics for Life Sciences, Medicine and Health, Epidemiology Public Health and Medical Statistics, Medicine, Statistics and Probability
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    Subjects:
    Statistics for Life Sciences, Medicine and Health, Epidemiology Public Health and Medical Statistics, Medicine, Statistics and Probability
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    Book description

    This textbook for a second course in basic statistics for undergraduates or first-year graduate students introduces linear regression models and describes other linear models including Poisson regression, logistic regression, proportional hazards regression, and nonparametric regression. Numerous examples drawn from the news and current events with an emphasis on health issues illustrate these concepts. Assuming only a pre-calculus background, the author keeps equations to a minimum and demonstrates all computations using SAS. Most of the programs and output are displayed in a self-contained way, with an emphasis on the interpretation of the output in terms of how it relates to the motivating example. Plenty of exercises conclude every chapter. All of the datasets and SAS programs are available from the book's website, along with other ancillary material.

    Reviews

    "The author is an established and immensely experienced biostatistical and statistical researcher, and an excellent educator and speaker. His skill in teaching and presentation is very obvious in the engaging, sometime humorous, and easily comprehensible presentation style of the book. I will definitely keep a copy of this book on hand for my nonstatistical collaborators and even undergraduate students interested in a lucid yet thorough introduction to day-to-day biostatistical methods and applied data analysis."
    Debajyoti Sinha, The American Statistician

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