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Author: John Aitchison
Publisher: CRC Press
ISBN: 1584882085
Category : Mathematics
Languages : en
Pages : 355
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Book Description
Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment. The authors present each consultative problem in its original form, then describe the process of problem formulation, develop the appropriate statistical models, and interpret the statistical analysis in the context of the real problem. Their treatment provides clear, accessible explanations of statistical methods. The text includes end-of-chapter exercises that help develop formulatory, analytic, and interpretative skills.
Author: John Aitchison
Publisher: CRC Press
ISBN: 1584882085
Category : Mathematics
Languages : en
Pages : 355
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Book Description
Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment. The authors present each consultative problem in its original form, then describe the process of problem formulation, develop the appropriate statistical models, and interpret the statistical analysis in the context of the real problem. Their treatment provides clear, accessible explanations of statistical methods. The text includes end-of-chapter exercises that help develop formulatory, analytic, and interpretative skills.
Author: Robert H. Riffenburgh
Publisher: Academic Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 680
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Book Description
Medicine deals with treatments that work often but not always, so treatment success must be based on probability. Statistical methods lift medical research from the anecdotal to measured levels of probability. This book presents the common statistical methods used in 90% of medical research, along with the underlying basics, in two parts: a textbook section for use by students in health care training programs, e.g., medical schools or residency training, and a reference section for use by practicing clinicians in reading medical literature and performing their own research. The book does not require a significant level of mathematical knowledge and couches the methods in multiple examples drawn from clinical medicine, giving it applicable context. Easy-to-follow format incorporates medical examples, step-by-step methods, and check yourself exercises Two-part design features course material and a professional reference section Chapter summaries provide a review of formulas, method algorithms, and check lists Companion site links to statistical databases that can be downloaded and used to perform the exercises from the book and practice statistical methods New in this Edition: New chapters on: multifactor tests on means of continuous data, equivalence testing, and advanced methods New topics include: trial randomization, treatment ethics in medical research, imputation of missing data, and making evidence-based medical decisions Updated database coverage and additional exercises Expanded coverage of numbers needed to treat and to benefit, and regression analysis including stepwise regression and Cox regression Thorough discussion on required sample size
Author: Martin Bland
Publisher: Oxford University Press
ISBN: 0192518399
Category : Medical
Languages : en
Pages : 737
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Book Description
Now in its Fourth Edition, An Introduction to Medical Statistics continues to be a 'must-have' textbook for anyone who needs a clear logical guide to the subject. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the statistical principles used in the medical literature. Taking readers through the common statistical methods seen in published research and guidelines, the text focuses on how to interpret and analyse statistics for clinical practice. Using extracts from real studies, the author illustrates how data can be employed correctly and incorrectly in medical research helping readers to evaluate the statistics they encounter and appropriately implement findings in clinical practice. End of chapter exercises, case studies and multiple choice questions help readers to apply their learning and develop their own interpretative skills. This thoroughly revised edition includes new chapters on meta-analysis, missing data, and survival analysis.
Author: Alfred Bartolucci
Publisher: John Wiley & Sons
ISBN: 1118736869
Category : Mathematics
Languages : en
Pages : 259
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Book Description
Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process Introduces terminology used in many applications such as the interpretation of assay design and validation as well as “fit for purpose” procedures including real world examples Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions
Author: Ewout W. Steyerberg
Publisher: Springer
ISBN: 3030163997
Category : Medical
Languages : en
Pages : 574
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Book Description
The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies
Author: Amir Momeni
Publisher: Springer
ISBN: 3319605437
Category : Medical
Languages : en
Pages : 322
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Book Description
This text provides a comprehensive and practical review of the main statistical methods in pathology and laboratory medicine. It introduces statistical concepts used in pathology and laboratory medicine. The information provided is relevant to pathologists both for their day to day clinical practice as well as in their research and scholarly activities. The text will begins by explaining the fundamentals concepts in statistics. In the later sections, these fundamental concepts are expanded and unique applications of statistical methods in pathology and laboratory medicine practice are introduced. Other sections of the text explain research methodology in pathology covering a broad range of topics from study design to analysis of data. Finally, data-heavy novel concepts that are emerging in pathology and pathology research are presented such as molecular pathology and pathology informatics. Introduction to Statistical Methods in Pathology will be of great value for pathologists, pathology residents, basic and translational researchers, laboratory managers and medical students.
Author: Andreas Ziegler
Publisher: John Wiley & Sons
ISBN: 3527633669
Category : Science
Languages : en
Pages : 522
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Book Description
A Statistical Approach to Genetic Epidemiology After studying statistics and mathematics at the University of Munich and obtaining his doctoral degree from the University of Dortmund, Andreas Ziegler received the Johann-Peter-Süssmilch-Medal of the German Association for Medical Informatics, Biometry and Epidemiology for his post-doctoral work on “Model Free Linkage Analysis of Quantitative Traits” in 1999. In 2004, he was one of the recipients of the Fritz-Linder-Forum-Award from the German Association for Surgery.
Author: Mitchell G. Maltenfort
Publisher: CRC Press
ISBN: 135160838X
Category : Mathematics
Languages : en
Pages : 153
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Book Description
Trying to read up on statistics can be like trying to decide where you want to start eating the elephant and what’s the most digestible way to get it down. This book is written to give bite-size nuggets of insight based on our experiences grappling with datasets large and small. It is intended to bridge the gap between the formal equations and the practicalities of generating a research manuscript. We won’t pretend reading it will answer all your questions but it will help explain what questions need to be asked for your study and how you can address them with both accuracy and clarity. The size, detail and (ostensible) organization of this book allow for easy reading and can give a leg (or at least a half-step) up for those seeking more detailed study later. Features include: Excel sheets to allow exploration of topics raised Emphasis on intuitive explanations over formulas. Consideration of issues specific to clinical and surgical studies Our audience is someone who may or may not have enjoyed formal statistics education (that is, you may have had it and not enjoyed it!) who may like seeing a more dressed-down presentation of the topics. Actual statisticians may pick this up at risk of a chuckle (with us or at us) and may find some useful ways to present topics to non-statisticians.
Author: John Aitchison
Publisher: CRC Press
ISBN: 0203497414
Category : Mathematics
Languages : en
Pages : 348
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Book Description
Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment. The authors present each consultative problem in its original form, then describe the process o
Author: Laurens Holmes, Jr.
Publisher: Routledge
ISBN: 1315352214
Category : Medical
Languages : en
Pages : 324
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Book Description
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.
