Statistical modeling for biomedical researchers - Info and Reading Options
a simple introduction to the analysis of complex data
By William D. Dupont

"Statistical modeling for biomedical researchers" was published by Cambridge University Press in 2002 - Cambridge, U.K, it has 386 pages and the language of the book is English.
“Statistical modeling for biomedical researchers” Metadata:
- Title: ➤ Statistical modeling for biomedical researchers
- Author: William D. Dupont
- Language: English
- Number of Pages: 386
- Publisher: Cambridge University Press
- Publish Date: 2002
- Publish Location: Cambridge, U.K
“Statistical modeling for biomedical researchers” Subjects and Themes:
- Subjects: ➤ Biometry - Data Interpretation, Statistical - Mathematical Computing - Mathematical models - Medicine - Methods - Models, Statistical - Problems and Exercises - Research - Statistical Data Interpretation - Statistical Models - Statistical methods - Methodology - Recherche - Interpretation statistique des donnees - MEDICAL - Estatistica aplicada - Biometrie - Biociencias - Informatique - Biostatistics - Modeles statistiques - Statistik - Medecine - Methodes statistiques - Calcul mathematique ordinateur - Medicine, research - Research, methodology - Medical statistics
Edition Specifications:
- Pagination: xvii, 386 p. :
Edition Identifiers:
- The Open Library ID: OL18184033M - OL12344218W
- Online Computer Library Center (OCLC) ID: 49942324
- Library of Congress Control Number (LCCN): 2002073487
- ISBN-10: 0521820618 - 0521655781
- All ISBNs: 0521820618 - 0521655781
AI-generated Review of “Statistical modeling for biomedical researchers”:
"Statistical modeling for biomedical researchers" Description:
The Open Library:
"This text will enable biomedical researchers to use a number of advanced statistical methods that have proven valuable in medical research. It is intended for people who have had an introductory course in biostatistics. A statistical software package (Stata) is used to avoid mathematics beyond the high school level. The emphasis is on understanding the assumptions underlying each method, using exploratory techniques to determine the most appropriate method, and presenting results in a way that will be readily understood by clinical colleagues. Graphical methods are used extensively. Topics covered include linear regression, logistic regression, Poisson regression, survival analysis, fixed-effects analysis of variance, and repeated-measures analysis of variance. Each method is introduced in its simplest form and is then extended to cover situations in which multiple explanatory variables are collected on each study subject."--BOOK JACKET.
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