Survival Analysis and Maximum Likelihood Techniques as Applied to Physiological Modeling PDF Download
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Author: Undersea and Hyperbaric Medical Society. Workshop
Publisher:
ISBN:
Category : Decompression sickness
Languages : en
Pages : 186
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Book Description
Author: Undersea and Hyperbaric Medical Society. Workshop
Publisher:
ISBN:
Category : Decompression sickness
Languages : en
Pages : 186
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Book Description
Author: Ryszard Klos
Publisher: CRC Press
ISBN: 1000853454
Category : Medical
Languages : en
Pages : 232
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Book Description
The book provides a derivation of the models used for calculating the risk and hazard of central oxygen toxicity pertaining to diving-based studies consistent with the research conducted earlier by the Royal Navy and the US Navy. This book forms the basis for extending the possibility of undertaking nitrox dives in combination with oxygen dives, thus significantly increasing tactical capabilities of conducting diving special operations. Features: provides derivation of the models used for calculating the risk and hazard of central oxygen toxicity improves oxygen diving procedures described in the US Navy Diving Manual includes procedures applicable to undertaking nitrox dives in combination with oxygen dives pitches the material at highest technology readiness levels, i.e. 9 TRL aims to increase tactical capabilities of conducting diving special operations This book is aimed at researchers, professionals and graduate students in life support system design, diving submarine safety, ventilation, health, sanitary engineering, mining engineering and working environment in chambers or closed compartments.
Author: Xian Liu
Publisher: John Wiley & Sons
ISBN: 1118307674
Category : Mathematics
Languages : en
Pages : 433
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Book Description
Survival analysis concerns sequential occurrences of events governed by probabilistic laws. Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis. Assumes only a minimal knowledge of SAS whilst enabling more experienced users to learn new techniques of data input and manipulation. Provides numerous examples of SAS code to illustrate each of the methods, along with step-by-step instructions to perform each technique. Highlights the strengths and limitations of each technique covered. Covering a wide scope of survival techniques and methods, from the introductory to the advanced, this book can be used as a useful reference book for planners, researchers, and professors who are working in settings involving various lifetime events. Scientists interested in survival analysis should find it a useful guidebook for the incorporation of survival data and methods into their projects.
Author: Gregory R. Hancock
Publisher: Routledge
ISBN: 1135172994
Category : Education
Languages : en
Pages : 449
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Book Description
Designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond, this title includes chapters that address traditional and emerging quantitative methods of data analysis.
Author: Rajender R. Aparasu
Publisher: Jones & Bartlett Publishers
ISBN: 1449691315
Category : Medical
Languages : en
Pages : 400
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Book Description
Principles of Research Design and Drug Literature Evaluation is a unique resource that provides a balanced approach covering critical elements of clinical research, biostatistical principles, and scientific literature evaluation techniques for evidence-based medicine. This accessible text provides comprehensive course content that meets and exceeds the curriculum standards set by the Accreditation Council for Pharmacy Education (ACPE). Written by expert authors specializing in pharmacy practice and research, this valuable text will provide pharmacy students and practitioners with a thorough understanding of the principles and practices of drug literature evaluation with a strong grounding in research and biostatistical principles. Principles of Research Design and Drug Literature Evaluation is an ideal foundation for professional pharmacy students and a key resource for pharmacy residents, research fellows, practitioners, and clinical researchers. FEATURES * Chapter Pedagogy: Learning Objectives, Review Questions, References, and Online Resources * Instructor Resources: PowerPoint Presentations, Test Bank, and an Answer Key * Student Resources: a Navigate Companion Website, including Crossword Puzzles, Interactive Flash Cards, Interactive Glossary, Matching Questions, and Web Links From the Foreword: "This book was designed to provide and encourage practitioner’s development and use of critical drug information evaluation skills through a deeper understanding of the foundational principles of study design and statistical methods. Because guidance on how a study’s limited findings should not be used is rare, practitioners must understand and evaluate for themselves the veracity and implications of the inherently limited primary literature findings they use as sources of drug information to make evidence-based decisions together with their patients. The editors organized the book into three supporting sections to meet their pedagogical goals and address practitioners’ needs in translating research into practice. Thanks to the editors, authors, and content of this book, you can now be more prepared than ever before for translating research into practice." L. Douglas Ried, PhD, FAPhA Editor-in-Chief Emeritus, Journal of the American Pharmacists Association Professor and Associate Dean for Academic Affairs, College of Pharmacy, University of Texas at Tyler, Tyler, Texas
Author: Murray A. Aitkin
Publisher: Oxford University Press, USA
ISBN: 9780198524137
Category : Computers
Languages : en
Pages : 584
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Book Description
"This text examines the theory of statistical modelling with generalised linear models. It also looks at applications of the theory to practical problems, using the GLIM4 package"--Provided by publisher.
Author: Paul D. Allison
Publisher: SAS Institute
ISBN: 1599948842
Category : Computers
Languages : en
Pages : 337
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Book Description
Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D. Allison, is an accessible, data-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with this fully updated new edition that incorporates the many enhancements in SAS procedures for survival analysis in SAS 9. Although the book assumes only a minimal knowledge of SAS, more experienced users will learn new techniques of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book, ensuring that even the uninitiated become sophisticated users of survival analysis. The main topics presented include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered in survival analysis books, such as time-dependent covariates, competing risks, and repeated events. Survival Analysis Using SAS: A Practical Guide, Second Edition, has been thoroughly updated for SAS 9, and all figures are presented using ODS Graphics. This new edition also documents major enhancements to the STRATA statement in the LIFETEST procedure; includes a section on the PROBPLOT command, which offers graphical methods to evaluate the fit of each parametric regression model; introduces the new BAYES statement for both parametric and Cox models, which allows the user to do a Bayesian analysis using MCMC methods; demonstrates the use of the counting process syntax as an alternative method for handling time-dependent covariates; contains a section on cumulative incidence functions; and describes the use of the new GLIMMIX procedure to estimate random-effects models for discrete-time data. This book is part of the SAS Press program.
Author: Thomas W. Miller
Publisher: Pearson Education
ISBN: 0133886018
Category : Business & Economics
Languages : en
Pages : 376
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Book Description
Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you're new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you're already a modeler, programmer, or manager, it will teach you crucial skills you don't yet have. This guide illuminates the discipline through realistic vignettes and intuitive data visualizations-not complex math. Thomas W. Miller, leader of Northwestern University's pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today's key applications for predictive analytics, delivering skills and knowledge to put models to work-and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively.
Author: Sarah Boslaugh
Publisher: SAGE
ISBN: 1412928168
Category : Medical
Languages : en
Pages : 1241
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Book Description
Presents information from the field of epidemiology in a less technical, more accessible format. Covers major topics in epidemiology, from risk ratios to case-control studies to mediating and moderating variables, and more. Relevant topics from related fields such as biostatistics and health economics are also included.
Author: Mike W.-L. Cheung
Publisher: John Wiley & Sons
ISBN: 1118957830
Category : Mathematics
Languages : en
Pages : 400
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Book Description
Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.
