Statistical Modeling In Biomedical Research PDF Download
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| Author | : Yichuan Zhao |
| Publisher | : Springer Nature |
| Total Pages | : 495 |
| Release | : 2020-03-19 |
| Genre | : Medical |
| ISBN | : 3030334163 |
Download Statistical Modeling in Biomedical Research Book in PDF, ePub and Kindle
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.
| Author | : William D. Dupont |
| Publisher | : Cambridge University Press |
| Total Pages | : 543 |
| Release | : 2009-02-12 |
| Genre | : Medical |
| ISBN | : 0521849527 |
Download Statistical Modeling for Biomedical Researchers Book in PDF, ePub and Kindle
A second edition of the easy-to-use standard text guiding biomedical researchers in the use of advanced statistical methods.
| Author | : |
| Publisher | : |
| Total Pages | : 495 |
| Release | : 2020 |
| Genre | : Biometry |
| ISBN | : 9783030334178 |
Download Statistical Modeling in Biomedical Research Book in PDF, ePub and Kindle
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.
| Author | : William Dudley Dupont |
| Publisher | : |
| Total Pages | : 544 |
| Release | : 2014-05-14 |
| Genre | : Medical |
| ISBN | : 9780511480904 |
Download Statistical Modeling for Biomedical Researchers Book in PDF, ePub and Kindle
New edition of the easy-to-use standard text guiding biomedical researchers in the use of advanced statistical methods.
| Author | : William D. Dupont |
| Publisher | : Cambridge University Press |
| Total Pages | : 543 |
| Release | : 2009-02-12 |
| Genre | : Medical |
| ISBN | : 1139643819 |
Download Statistical Modeling for Biomedical Researchers Book in PDF, ePub and Kindle
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/.
| Author | : J. Philip Miller |
| Publisher | : Elsevier |
| Total Pages | : 363 |
| Release | : 2010-11-08 |
| Genre | : Mathematics |
| ISBN | : 0444537384 |
Download Essential Statistical Methods for Medical Statistics Book in PDF, ePub and Kindle
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
| Author | : Filia Vonta |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 556 |
| Release | : 2008-03-05 |
| Genre | : Medical |
| ISBN | : 0817646191 |
Download Statistical Models and Methods for Biomedical and Technical Systems Book in PDF, ePub and Kindle
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.
| Author | : Henry Horng-Shing Lu |
| Publisher | : Springer Nature |
| Total Pages | : 406 |
| Release | : 2022-12-08 |
| Genre | : Science |
| ISBN | : 3662659026 |
Download Handbook of Statistical Bioinformatics Book in PDF, ePub and Kindle
Now in its second edition, this handbook collects authoritative contributions on modern methods and tools in statistical bioinformatics with a focus on the interface between computational statistics and cutting-edge developments in computational biology. The three parts of the book cover statistical methods for single-cell analysis, network analysis, and systems biology, with contributions by leading experts addressing key topics in probabilistic and statistical modeling and the analysis of massive data sets generated by modern biotechnology. This handbook will serve as a useful reference source for students, researchers and practitioners in statistics, computer science and biological and biomedical research, who are interested in the latest developments in computational statistics as applied to computational biology.
| Author | : James D. Malley |
| Publisher | : Cambridge University Press |
| Total Pages | : 301 |
| Release | : 2011-02-24 |
| Genre | : Medical |
| ISBN | : 1139496859 |
Download Statistical Learning for Biomedical Data Book in PDF, ePub and Kindle
This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random ForestsTM, neural nets, support vector machines, nearest neighbors and boosting.
| Author | : Ding-Geng (Din) Chen |
| Publisher | : Springer |
| Total Pages | : 354 |
| Release | : 2015-08-31 |
| Genre | : Medical |
| ISBN | : 3319185365 |
Download Innovative Statistical Methods for Public Health Data Book in PDF, ePub and Kindle
The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference and it can be used in graduate level classes.
