Statistical Modeling for Biomedical Researchers

Statistical Modeling for Biomedical Researchers

Author: William D. Dupont

Publisher: Cambridge University Press

Published: 2009-02-12

Total Pages:

ISBN-13: 1139643819

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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/.


Book Synopsis Statistical Modeling for Biomedical Researchers by : William D. Dupont

Download or read book Statistical Modeling for Biomedical Researchers written by William D. Dupont and published by Cambridge University Press. This book was released on 2009-02-12 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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/.

Statistical Modeling for Biomedical Researchers

Statistical Modeling for Biomedical Researchers

Author: William Dudley Dupont

Publisher:

Published: 2002

Total Pages: 386

ISBN-13: 9780521820615

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This text enables biomedical researchers to use a number of advanced statistical methods that have proven valuable in medical research, and uses a statistical software package (Stata(R) ) to avoid mathematics beyond the high school level. Intended for people who have had an introductory course in biostatistics, the volume emphasizes the assumptions underlying each method, using exploratory techniques to determine the most appropriate method. It presents results in a way that will be readily understood by clinical colleagues. Numerous real examples from medical literature and graphical methods are used to illustrate these techniques.


Book Synopsis Statistical Modeling for Biomedical Researchers by : William Dudley Dupont

Download or read book Statistical Modeling for Biomedical Researchers written by William Dudley Dupont and published by . This book was released on 2002 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text enables biomedical researchers to use a number of advanced statistical methods that have proven valuable in medical research, and uses a statistical software package (Stata(R) ) to avoid mathematics beyond the high school level. Intended for people who have had an introductory course in biostatistics, the volume emphasizes the assumptions underlying each method, using exploratory techniques to determine the most appropriate method. It presents results in a way that will be readily understood by clinical colleagues. Numerous real examples from medical literature and graphical methods are used to illustrate these techniques.

Statistical Modeling for Biomedical Researchers

Statistical Modeling for Biomedical Researchers

Author:

Publisher:

Published: 2009

Total Pages: 522

ISBN-13: 9780511480102

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New edition of the easy-to-use standard text guiding biomedical researchers in the use of advanced statistical methods.


Book Synopsis Statistical Modeling for Biomedical Researchers by :

Download or read book Statistical Modeling for Biomedical Researchers written by and published by . This book was released on 2009 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: New edition of the easy-to-use standard text guiding biomedical researchers in the use of advanced statistical methods.

Statistical Modeling in Biomedical Research

Statistical Modeling in Biomedical Research

Author: Yichuan Zhao

Publisher: Springer Nature

Published: 2020-03-19

Total Pages: 495

ISBN-13: 3030334163

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This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications Large scale data analysis and its applications Biomedical research and modeling Survival analysis with complex data structure and its applications.


Book Synopsis Statistical Modeling in Biomedical Research by : Yichuan Zhao

Download or read book Statistical Modeling in Biomedical Research written by Yichuan Zhao and published by Springer Nature. This book was released on 2020-03-19 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications Large scale data analysis and its applications Biomedical research and modeling Survival analysis with complex data structure and its applications.

Statistical Modeling in Biomedical Research

Statistical Modeling in Biomedical Research

Author:

Publisher:

Published: 2020

Total Pages: 495

ISBN-13: 9783030334178

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This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications Large scale data analysis and its applications Biomedical research and modeling Survival analysis with complex data structure and its applications.


Book Synopsis Statistical Modeling in Biomedical Research by :

Download or read book Statistical Modeling in Biomedical Research written by and published by . This book was released on 2020 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications Large scale data analysis and its applications Biomedical research and modeling Survival analysis with complex data structure and its applications.

Statistical Methods for the Analysis of Biomedical Data

Statistical Methods for the Analysis of Biomedical Data

Author: Robert F. Woolson

Publisher: John Wiley & Sons

Published: 2011-01-25

Total Pages: 714

ISBN-13: 111803130X

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Dieser Band behandelt eine Reihe statistischer Themen, die bei der Analyse biologischer und medizinischer Daten allgemein Anwendung finden. Diese 2. Auflage wurde komplett überarbeitet, aktualisiert und erweitert. Einige Kapitel sind neu hinzugekommen, u.a. zur multiplen linearen Regression in der biomedizinischen Forschung. Der Stoff ist so gegliedert, dass der Leser den Text unabhängig von der jeweiligen statistischen Methode leicht nach Problemstellungen durchsuchen kann. Mit zahlreichen durchgearbeiteten Beispielen, die detaillierte Lösungsangaben zu Problemen aus der Praxis liefern.


Book Synopsis Statistical Methods for the Analysis of Biomedical Data by : Robert F. Woolson

Download or read book Statistical Methods for the Analysis of Biomedical Data written by Robert F. Woolson and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dieser Band behandelt eine Reihe statistischer Themen, die bei der Analyse biologischer und medizinischer Daten allgemein Anwendung finden. Diese 2. Auflage wurde komplett überarbeitet, aktualisiert und erweitert. Einige Kapitel sind neu hinzugekommen, u.a. zur multiplen linearen Regression in der biomedizinischen Forschung. Der Stoff ist so gegliedert, dass der Leser den Text unabhängig von der jeweiligen statistischen Methode leicht nach Problemstellungen durchsuchen kann. Mit zahlreichen durchgearbeiteten Beispielen, die detaillierte Lösungsangaben zu Problemen aus der Praxis liefern.

Applied Biostatistical Principles and Concepts

Applied Biostatistical Principles and Concepts

Author: Laurens Holmes, Jr.

Publisher: Routledge

Published: 2017-11-22

Total Pages: 288

ISBN-13: 1498741207

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The past three decades have witnessed modern advances in statistical modeling and evidence discovery in biomedical, clinical, and population-based research. With these advances come the challenges in accurate model stipulation and application of models in scientific evidence discovery Applied Biostatistical Principles and Concepts provides practical knowledge using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics in attempt to improve the health of patients and populations. This book is suitable for both clinicians and health or biological sciences students. It presents the reality in statistical modelling of health research data in a concise manner that will address the issue of "big data" type I error tolerance and probability value, effect size and confidence interval for precision, effect measure modification and interaction as well as confounders, thus allowing for more valid inferences and yielding results that are more reliable, valid and accurate.


Book Synopsis Applied Biostatistical Principles and Concepts by : Laurens Holmes, Jr.

Download or read book Applied Biostatistical Principles and Concepts written by Laurens Holmes, Jr. and published by Routledge. This book was released on 2017-11-22 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past three decades have witnessed modern advances in statistical modeling and evidence discovery in biomedical, clinical, and population-based research. With these advances come the challenges in accurate model stipulation and application of models in scientific evidence discovery Applied Biostatistical Principles and Concepts provides practical knowledge using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics in attempt to improve the health of patients and populations. This book is suitable for both clinicians and health or biological sciences students. It presents the reality in statistical modelling of health research data in a concise manner that will address the issue of "big data" type I error tolerance and probability value, effect size and confidence interval for precision, effect measure modification and interaction as well as confounders, thus allowing for more valid inferences and yielding results that are more reliable, valid and accurate.

Essential Statistical Methods for Medical Statistics

Essential Statistical Methods for Medical Statistics

Author: J. Philip Miller

Publisher: Elsevier

Published: 2010-11-08

Total Pages: 368

ISBN-13: 9780444537386

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Essential Statistical Methods for Medical Statistics presents only key contributions which have been selected from the volume in the Handbook of Statistics: Medical Statistics, Volume 27 (2009). While the use of statistics in these fields has a long and rich history, the explosive growth of science in general, and of clinical and epidemiological sciences in particular, has led to the development of new methods and innovative adaptations of standard methods. This volume is appropriately focused for individuals working in these fields. Contributors are internationally renowned experts in their respective areas. · Contributors are internationally renowned experts in their respective areas · Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research · Methods for assessing Biomarkers, analysis of competing risks · Clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs · Structural equations modelling and longitudinal data analysis


Book Synopsis Essential Statistical Methods for Medical Statistics by : J. Philip Miller

Download or read book Essential Statistical Methods for Medical Statistics written by J. Philip Miller and published by Elsevier. This book was released on 2010-11-08 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential Statistical Methods for Medical Statistics presents only key contributions which have been selected from the volume in the Handbook of Statistics: Medical Statistics, Volume 27 (2009). While the use of statistics in these fields has a long and rich history, the explosive growth of science in general, and of clinical and epidemiological sciences in particular, has led to the development of new methods and innovative adaptations of standard methods. This volume is appropriately focused for individuals working in these fields. Contributors are internationally renowned experts in their respective areas. · Contributors are internationally renowned experts in their respective areas · Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research · Methods for assessing Biomarkers, analysis of competing risks · Clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs · Structural equations modelling and longitudinal data analysis

Regression Modeling Strategies

Regression Modeling Strategies

Author: Frank E. Harrell

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 583

ISBN-13: 147573462X

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Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".


Book Synopsis Regression Modeling Strategies by : Frank E. Harrell

Download or read book Regression Modeling Strategies written by Frank E. Harrell and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".

Statistical Models and Methods for Biomedical and Technical Systems

Statistical Models and Methods for Biomedical and Technical Systems

Author: Filia Vonta

Publisher: Springer Science & Business Media

Published: 2008-03-05

Total Pages: 556

ISBN-13: 0817646191

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This book deals with the mathematical aspects of survival analysis and reliability as well as other topics, reflecting recent developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; models and methods in survival analysis, longevity, aging, and degradation; accelerated life models; quality of life; new statistical challenges in genomics. The work will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering.


Book Synopsis Statistical Models and Methods for Biomedical and Technical Systems by : Filia Vonta

Download or read book Statistical Models and Methods for Biomedical and Technical Systems written by Filia Vonta and published by Springer Science & Business Media. This book was released on 2008-03-05 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the mathematical aspects of survival analysis and reliability as well as other topics, reflecting recent developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; models and methods in survival analysis, longevity, aging, and degradation; accelerated life models; quality of life; new statistical challenges in genomics. The work will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering.