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Multivariable analysis [Book] : a practical guide for clinicians / Mitchell H. Katz.

By: Material type: TextTextPublication details: New York : New York : Cambridge University Press, 1999.Description: xv, 192 p. : ill. ; 24 cmISBN:
  • 0521593018 (hbk)
Subject(s): DDC classification:
  • 610.727 21
Other classification:
  • 610.727
Summary: Multivariable analysis is a challenging subject for clinicians, whether they are novice researchers or trained practitioners. Most basic biostatistics books do not cover multivariable analysis, while existing multivariable analysis books are dense with mathematical formulas. Multivariable Analysis: A Practical Guide for Clinicians steps aside from mathematics and offers conceptual explanations. Dr. Mitchell Katz follows a nonthreatening, question-and-answer approach to explain how to perform and interpret multivariable analyses. He begins by explaining why clinicians should do multivariable analyses and then guides the reader through topics such as how to choose which type of multivariable method to perform, how to deal with missing data, and how to validate multivariable models. The book is loaded with useful tips, tables, figures, and references. Examples from the medical literature demonstrate several real-world applications and uses of multivariable analysis. This book will prove to be an indispensable guide for medical students, residents, and practicing physicians.
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Includes index

Multivariable analysis is a challenging subject for clinicians, whether they are novice researchers or trained practitioners. Most basic biostatistics books do not cover multivariable analysis, while existing multivariable analysis books are dense with mathematical formulas. Multivariable Analysis: A Practical Guide for Clinicians steps aside from mathematics and offers conceptual explanations. Dr. Mitchell Katz follows a nonthreatening, question-and-answer approach to explain how to perform and interpret multivariable analyses. He begins by explaining why clinicians should do multivariable analyses and then guides the reader through topics such as how to choose which type of multivariable method to perform, how to deal with missing data, and how to validate multivariable models. The book is loaded with useful tips, tables, figures, and references. Examples from the medical literature demonstrate several real-world applications and uses of multivariable analysis. This book will prove to be an indispensable guide for medical students, residents, and practicing physicians.

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