Statistical Methods For The Analysis Of Biomedical Data
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Statistical Methods For The Analysis Of Biomedical Data
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Author : Robert F. Woolson
language : en
Publisher: John Wiley & Sons
Release Date : 2011-01-25
Statistical Methods For The Analysis Of Biomedical Data written by Robert F. Woolson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-25 with Medical categories.
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.
Statistical Learning For Biomedical Data
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Author : James D. Malley
language : en
Publisher: Cambridge University Press
Release Date : 2011-02-24
Statistical Learning For Biomedical Data written by James D. Malley and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-24 with Medical categories.
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.
Statistical Methods For Biomedical Research
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Author : Ji-qian Fang
language : en
Publisher: World Scientific
Release Date : 2021-03-18
Statistical Methods For Biomedical Research written by Ji-qian Fang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-18 with Medical categories.
This book consists of four parts with 32 chapters adapted for four short courses, from the basic to the advanced levels of medical statistics (biostatistics), ideal for biomedical students. Part 1 is a compulsory course of Basic Statistics with descriptive statistics, parameter estimation and hypothesis test, simple correlation and regression. Part 2 is a selective course on Study Design and Implementation with sampling survey, interventional study, observational study, diagnosis study, data sorting and article writing. Part 3 is a specially curated course of Multivariate Analyses with complex analyses of variance, variety of regressions and classical multivariate analyses. Part 4 is a seminar course on Introduction to Advanced Statistical Methods with meta-analysis, time series, item response theory, structure equation model, multi-level model, bio-informatics, genetic statistics and data mining.The main body of each chapter is followed by five practical sections: Report Writing, Case Discrimination, Computer Experiments, Frequently Asked Questions and Summary, and Practice & Think. Moreover, there are 2 attached Appendices, Appendix A includes Introductions to SPSS, Excel and R respectively, and Appendix B includes all the programs, data and printouts for Computer Experiments in addition to the Tests for Review and the reference answers for Case Discrimination as well as Practice & Think..This book can be used as a textbook for biomedical students at both under- and postgraduate levels. It can also serve as an important guide for researchers, professionals and officers in the biomedical field.
Innovative Statistical Methods For Public Health Data
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Author : Ding-Geng (Din) Chen
language : en
Publisher: Springer
Release Date : 2015-08-31
Innovative Statistical Methods For Public Health Data written by Ding-Geng (Din) Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-31 with Medical categories.
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.
Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques
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Author :
language : en
Publisher:
Release Date :
Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Statistical Modeling For Biomedical Researchers
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Author : William D. Dupont
language : en
Publisher: Cambridge University Press
Release Date : 2009-02-12
Statistical Modeling For Biomedical Researchers written by William D. Dupont and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-12 with Medical categories.
A second edition of the easy-to-use standard text guiding biomedical researchers in the use of advanced statistical methods.
Statistical Modeling In Biomedical Research
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Author : Yichuan Zhao
language : en
Publisher: Springer Nature
Release Date : 2020-03-19
Statistical Modeling In Biomedical Research written by Yichuan Zhao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-19 with Medical categories.
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 In Medical Research
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Author : Peter Armitage
language : en
Publisher: John Wiley & Sons
Release Date : 2013-07-01
Statistical Methods In Medical Research written by Peter Armitage and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-01 with Medical categories.
The explanation and implementation of statistical methods for themedical researcher or statistician remains an integral part ofmodern medical research. This book explains the use of experimentaland analytical biostatistics systems. Its accessible style allowsit to be used by the non-mathematician as a fundamental componentof successful research. Since the third edition, there have been many developments instatistical techniques. The fourth edition provides the medicalstatistician with an accessible guide to these techniques and toreflect the extent of their usage in medical research. The new edition takes a much more comprehensive approach to itssubject. There has been a radical reorganization of the text toimprove the continuity and cohesion of the presentation and toextend the scope by covering many new ideas now being introducedinto the analysis of medical research data. The authors have triedto maintain the modest level of mathematical exposition thatcharacterized the earlier editions, essentially confining themathematics to the statement of algebraic formulae rather thanpursuing mathematical proofs. Received the Highly Commended Certificate in the PublicHealth Category of the 2002 BMA BooksCompetition.
Statistical Analysis Of High Dimensional Biomedical Data A Gentle Introduction To Analytical Goals Common Approaches And Challenges
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Author : Jörg Rahnenführer
language : en
Publisher:
Release Date : 2023
Statistical Analysis Of High Dimensional Biomedical Data A Gentle Introduction To Analytical Goals Common Approaches And Challenges written by Jörg Rahnenführer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Abstract: Background In high-dimensional data (HDD) settings, the number of variables associated with each observation is very large. Prominent examples of HDD in biomedical research include omics data with a large number of variables such as many measurements across the genome, proteome, or metabolome, as well as electronic health records data that have large numbers of variables recorded for each patient. The statistical analysis of such data requires knowledge and experience, sometimes of complex methods adapted to the respective research questions. Methods Advances in statistical methodology and machine learning methods offer new opportunities for innovative analyses of HDD, but at the same time require a deeper understanding of some fundamental statistical concepts. Topic group TG9 "High-dimensional data" of the STRATOS (STRengthening Analytical Thinking for Observational Studies) initiative provides guidance for the analysis of observational studies, addressing particular statistical challenges and opportunities for the analysis of studies involving HDD. In this overview, we discuss key aspects of HDD analysis to provide a gentle introduction for non-statisticians and for classically trained statisticians with little experience specific to HDD. Results The paper is organized with respect to subtopics that are most relevant for the analysis of HDD, in particular initial data analysis, exploratory data analysis, multiple testing, and prediction. For each subtopic, main analytical goals in HDD settings are outlined. For each of these goals, basic explanations for some commonly used analysis methods are provided. Situations are identified where traditional statistical methods cannot, or should not, be used in the HDD setting, or where adequate analytic tools are still lacking. Many key references are provided. Conclusions This review aims to provide a solid statistical foundation for researchers, including statisticians and non-statisticians, who are new to research with HDD or simply want to better evaluate and understand the results of HDD analyses
Statistical Methods For Survival Data Analysis
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Author : Elisa T. Lee
language : en
Publisher: John Wiley & Sons
Release Date : 2003-08-01
Statistical Methods For Survival Data Analysis written by Elisa T. Lee and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-08-01 with Mathematics categories.
Third Edition brings the text up to date with new material and updated references. New content includes an introduction to left and interval censored data; the log-logistic distribution; estimation procedures for left and interval censored data; parametric methods iwth covariates; Cox's proportional hazards model (including stratification and time-dependent covariates); and multiple responses to the logistic regression model. Coverage of graphical methods has been deleted. Large data sets are provided on an FTP site for readers' convenience. Bibliographic remarks conclude each chapter.