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Statistical Methods in Medical Research

Statistical Methods in Medical Research Author Peter Armitage
ISBN-10 9781118702581
Release 2013-07-01
Pages 832
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The explanation and implementation of statistical methods for the medical researcher or statistician remains an integral part of modern medical research. This book explains the use of experimental and analytical biostatistics systems. Its accessible style allows it to be used by the non-mathematician as a fundamental component of successful research. Since the third edition, there have been many developments in statistical techniques. The fourth edition provides the medical statistician with an accessible guide to these techniques and to reflect the extent of their usage in medical research. The new edition takes a much more comprehensive approach to its subject. There has been a radical reorganization of the text to improve the continuity and cohesion of the presentation and to extend the scope by covering many new ideas now being introduced into the analysis of medical research data. The authors have tried to maintain the modest level of mathematical exposition that characterized the earlier editions, essentially confining the mathematics to the statement of algebraic formulae rather than pursuing mathematical proofs. Received the Highly Commended Certificate in the Public Health Category of the 2002 BMA Books Competition.



Statistical Methods in Medical Research

Statistical Methods in Medical Research Author Peter Armitage
ISBN-10 9781118702581
Release 2013-07-01
Pages 832
Download Link Click Here

The explanation and implementation of statistical methods for the medical researcher or statistician remains an integral part of modern medical research. This book explains the use of experimental and analytical biostatistics systems. Its accessible style allows it to be used by the non-mathematician as a fundamental component of successful research. Since the third edition, there have been many developments in statistical techniques. The fourth edition provides the medical statistician with an accessible guide to these techniques and to reflect the extent of their usage in medical research. The new edition takes a much more comprehensive approach to its subject. There has been a radical reorganization of the text to improve the continuity and cohesion of the presentation and to extend the scope by covering many new ideas now being introduced into the analysis of medical research data. The authors have tried to maintain the modest level of mathematical exposition that characterized the earlier editions, essentially confining the mathematics to the statement of algebraic formulae rather than pursuing mathematical proofs. Received the Highly Commended Certificate in the Public Health Category of the 2002 BMA Books Competition.



Essential Statistical Methods for Medical Statistics

Essential Statistical Methods for Medical Statistics Author J. Philip Miller
ISBN-10 0444537384
Release 2010-11-08
Pages 368
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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



Statistical Methods in Diagnostic Medicine

Statistical Methods in Diagnostic Medicine Author Xiao-Hua Zhou
ISBN-10 9781118626047
Release 2014-08-21
Pages 592
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Praise for the First Edition " . . . the book is a valuable addition to the literature in the field, serving as a much-needed guide for both clinicians and advanced students."—Zentralblatt MATH A new edition of the cutting-edge guide to diagnostic tests in medical research In recent years, a considerable amount of research has focused on evolving methods for designing and analyzing diagnostic accuracy studies. Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations. Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic accuracy, describe strategies for designing diagnostic accuracy studies, and present key statistical methods for estimating and comparing test accuracy. Topics new to the Second Edition include: Methods for tests designed to detect and locate lesions Recommendations for covariate-adjustment Methods for estimating and comparing predictive values and sample size calculations Correcting techniques for verification and imperfect standard biases Sample size calculation for multiple reader studies when pilot data are available Updated meta-analysis methods, now incorporating random effects Three case studies thoroughly showcase some of the questions and statistical issues that arise in diagnostic medicine, with all associated data provided in detailed appendices. A related web site features Fortran, SAS®, and R software packages so that readers can conduct their own analyses. Statistical Methods in Diagnostic Medicine, Second Edition is an excellent supplement for biostatistics courses at the graduate level. It also serves as a valuable reference for clinicians and researchers working in the fields of medicine, epidemiology, and biostatistics.



Statistical methods in medical research

Statistical methods in medical research Author Donald Mainland
ISBN-10 UOM:39015017400501
Release 1948
Pages 166
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Statistical methods in medical research has been writing in one form or another for most of life. You can find so many inspiration from Statistical methods in medical research also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Statistical methods in medical research book for free.



Practical Statistics for Medical Research

Practical Statistics for Medical Research Author Douglas G. Altman
ISBN-10 0412276305
Release 1990-11-22
Pages 624
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Most medical researchers, whether clinical or non-clinical, receive some background in statistics as undergraduates. However, it is most often brief, a long time ago, and largely forgotten by the time it is needed. Furthermore, many introductory texts fall short of adequately explaining the underlying concepts of statistics, and often are divorced from the reality of conducting and assessing medical research. Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. The text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.



Advanced Medical Statistics

Advanced Medical Statistics Author Ying Lu
ISBN-10 9789814583329
Release 2015-06-29
Pages 1472
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The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. Since the publication of the first edition, there have been tremendous advances in biostatistics and bioinformatics. The new edition tries to cover as many important emerging areas and reflect as much progress as possible. Many distinguished scholars, who greatly advanced their research areas in statistical methodology as well as practical applications, also have revised several chapters with relevant updates and written new ones from scratch. The new edition has been divided into four sections, including, Statistical Methods in Medicine and Epidemiology, Statistical Methods in Clinical Trials, Statistical Genetics, and General Methods. To reflect the rise of modern statistical genetics as one of the most fertile research areas since the publication of the first edition, the brand new section on Statistical Genetics includes entirely new chapters reflecting the state of the art in the field. Although tightly related, all the book chapters are self-contained and can be read independently. The book chapters intend to provide a convenient launch pad for readers interested in learning a specific topic, applying the related statistical methods in their scientific research and seeking the newest references for in-depth research. Contents:Statistics in Medicine and Epidemiology:History of Statistical Thinking in Medicine (Tar Timothy Chen)Describing Data, Modeling Variation, and Statistical Practice (Hongyan Du and Ming T Tan)Covariate-Specific and Covariate-Adjusted Predictive Values of Prognostic Biomarkers with Survival Outcome (Yunbei Ma, Xiao-Hua Zhou and Kwun Chuen (Gary) Chan)Statistical Methods for Personalized Medicine (Lu Tian and Xiaoguang Zhao)Statistics Used in Quality Control, Quality Assurance, and Quality Improvement in Radiological Studies (Ying Lu and Shoujun Zhao)Applications of Statistical Methods in Medical Imaging (Jesse S Jin)Cost-Effectiveness Analysis and Evidence-Based Medicine (Jianli Li)Quality of Life: Issues Concerning Assessment and Analysis (Jiqian Fang and Yuantao Hao)Meta-Analysis (Xuyu Zhou, Jiqian Fang, Chuanhua Yu, Zongli Xu, Lu Tian, and Ying Lu)Statistical Models and Methods in Infectious Diseases (Hulin Wu and Shoujun Zhao)Special Models for Sampling Survey (Sujuan Gao)The Use of Capture–Recapture Methodology in Epidemiological Surveillance and Ecological Surveys (Anne Chao, T C Hsieh and Hsin-Chou Yang)Statistical Methods in the Effective Evaluation of Mass Screening for Diseases (Qing Liu)Statistics in Clinical Trials:Statistics in Biopharmaceutical Research and Development (Shein-Chung Chow and Annpey Pong)Statistics in Pharmacology and Pre-Clinical Studies (Tze Leung Lai, Mei-Chiung Shin and Guangrui Zhu)Statistics in Toxicology (James J Chen)Dose-Response Modeling and Benchmark Doses in Health Risk Assessment (Yiliang Zhu)Some Fundamental Statistical Issues and Methodologies in Confirmatory Trials (George Y H Chi, Haiyan Xu and Qing Liu)Surrogates for Qualitative Evaluation of Treatment Effects (Zhi Geng)Adaptive Trial Design in Clinical Research (Annpey Pong and Shein-Chung Chow)Statistics in the Research of Traditional Chinese Medicine (Danhui Yi and Yang Li)Statistical Genetics:Sparse Segment Identifications with Applications to DNA Copy Number Variation Analysis (X Jessie Jeng, T Tony Cai and Hongzhe Li)Statistical Methods for Design and Analysis of Linkage Studies (Qizhai Li, Hong Qin, Zhaohai Li, and Gang Zheng)Transcriptome Analysis Using Next-Generation Sequencing (Jingyi Jessica Li, Haiyan Huang, Minping Qian and Xuegong Zhang)Genetic Structure of Human Population (Hua Tang and Kun Tang)Data Integration Methods in Genome Wide Association Studies (Ning Sun and Hongyu Zhao)Causal Inference (Zhi Geng)General Methods:Survival Analysis (D Y Lin)Nonparametric Regression Models for the Analysis of Longitudinal Data (Colin O Wu, Xin Tian, Kai F Yu, and Mi-Xia Wu)Local Modeling: Density Estimation and Nonparametric Regression (Jianqing Fan and Runze Li)Statistical Methods for Dependent Data (Feng Chen)Bayesian Methods (Ming-Hui Chen and Keying Ye)Valid Prior-Free Probabilistic Inference and Its Applications in Medical Statistics (Duncan Ermini Leaf, Hyokun Yun, and Chuanhai Liu)Stochastic Processes and Their Applications in Medical Science (Caixia Li and Jiqian Fang)Interpolation of Missing Values and Adjustment of Moving Holiday Effect in Time Series (Zhang Jin-Xin, Zhang Xi, Xue Yun-Lian, Li Ji-Bin and Huang Bo)Tree-based Methods (Heping Zhang)Introduction to Artificial Neural Networks (Xia Jielai, Jiang Hongwei, and Tang Qiyi) Readership: Biostatisticians, applied statisticians, medical researchers and clinicians, biopharmaceutical researchers, public health epidemiologists, biometricians and applied mathematicians. Key Features: The book covers very broad topics in medical statistics The book covers both most recent developments as well as classical work of the selected areas The book chapter is written by the experts in the field and illustrated with real life examplesKeywords:Medicine;Statistics;Epidemiology;Genomics;Clinical Trials;Bioinformatics;Machine Learning;Statistical Theory;Public HealthReviews: Review of the First Edition: “Overall the book covers a wide variety of applications. Each method is presented in sufficient depth to allow the reader to understand when the method(s) can be used … this book would be a useful resource for any practitioner in medical research.” Statistical Methods in Medical Research



Common Statistical Methods for Clinical Research with SAS Examples

Common Statistical Methods for Clinical Research with SAS Examples Author Glenn A. Walker
ISBN-10 9781607644255
Release 2010-02
Pages 552
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Thoroughly updated edition of the popular introductory statistics book for clinical researchers. This new edition has been extensively updated to include the use of ODS graphics in numerous examples as well as a new emphasis on PROC MIXED.



Translational Medicine

Translational Medicine Author Dennis Cosmatos
ISBN-10 1584888733
Release 2008-12-17
Pages 224
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Examines Critical Decisions for Transitioning Lab Science to a Clinical Setting The development of therapeutic pharmaceutical compounds is becoming more expensive, and the success rates for getting such treatments approved for marketing and to the patients is decreasing. As a result, translational medicine (TM) is becoming increasingly important in the healthcare industry – a means of maximizing the consideration and use of information collected as compounds transition from initial lab discovery, through pre-clinical testing, early clinical trials, and late confirmatory studies that lead to regulatory approval of drug release to patients. Translational Medicine: Strategies and Statistical Methods suggests a process for transitioning from the initial lab discovery to the patient’s bedside with minimal disconnect and offers a comprehensive review of statistical design and methodology commonly employed in this bench-to-bedside research. Documents Alternative Research Approaches for Faster and More Accurate Data Judgment Calls Elaborating on how to introduce TM into clinical studies, this authoritative work presents a keen approach to building, executing, and validating statistical models that consider data from various phases of development. It also delineates a truly translational example to help bolster understanding of discussed concepts. This comprehensive guide effectively demonstrates how to overcome obstacles related to successful TM practice. It contains invaluable information for pharmaceutical scientists, research executives, clinicians, and biostatisticians looking to expedite successful implementation of this important process.



Tutorials in Biostatistics Statistical Methods in Clinical Studies

Tutorials in Biostatistics  Statistical Methods in Clinical Studies Author Ralph B. D'Agostino
ISBN-10 9780470023662
Release 2005-09-27
Pages 466
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The Tutorials in Biostatistics have become a very popular feature of the prestigious Wiley journal, Statistics in Medicine (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with limited statistical knowledge. This book represents the first of two volumes presenting the best tutorials published in SIM, focusing on statistical methods in clinical studies. Topics include the design and analysis of clinical trials, epidemiology, survival analysis, and data monitoring. Each tutorial is focused on a medical problem, has been fully peer-reviewed and edited, and is authored by leading researchers in biostatistics. Many articles include an appendix on the latest developments since publication in the journal and additional references. This will appeal to statisticians working in medical research, as well as statistically-minded clinicians, biologists, epidemiologists and geneticists. It will also appeal to graduate students of biostatistics.



Statistical Methods in Medical Research

Statistical Methods in Medical Research Author Charan Singh Rayat
ISBN-10 9811308268
Release 2018-10-11
Pages
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This book covers all aspects of statistical methods in detail with applications. It presents solutions to the needs of post-graduate medical students, doctors and basic medical scientists for statistical evaluation of data. In present era, dependency on softwares for statistical analysis is eroding the basic understanding of the statistical methods and their applications. As a result, there are very few basic medical scientists capable of analyzing their research data due to lack of knowledge and ability. This book has been written in systematic way supported by figures and tables for basic understanding of various terms, definitions, formulae and applications of statistical methods with solved examples and graphic presentation of data to create interest in this mathematical science.



Regression Methods for Medical Research

Regression Methods for Medical Research Author Bee Choo Tai
ISBN-10 9781118721988
Release 2013-10-09
Pages 312
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Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures. The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the key design questions posed and in so doing take due account of any effects of potentially influencing co-variables. It begins with a revision of basic statistical concepts, followed by a gentle introduction to the principles of statistical modelling. The various methods of modelling are covered in a non-technical manner so that the principles can be more easily applied in everyday practice. A chapter contrasting regression modelling with a regression tree approach is included. The emphasis is on the understanding and the application of concepts and methods. Data drawn from published studies are used to exemplify statistical concepts throughout. Regression Methods for Medical Research is especially designed for clinicians, public health and environmental health professionals, para-medical research professionals, scientists, laboratory-based researchers and students.



Statistical Methods in Laboratory Medicine

Statistical Methods in Laboratory Medicine Author P. W. Strike
ISBN-10 9781483161921
Release 2014-05-16
Pages 552
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Statistical Methods in Laboratory Medicine focuses on the application of statistics in laboratory medicine. The book first ponders on quantitative and random variables, exploratory data analysis (EDA), probability, and probability distributions. Discussions focus on negative binomial distribution, non-random distributions, binomial distribution, fitting the binomial model to sample data, conditional probability and statistical independence, rules of probability, and Bayes' theorem. The text then examines inference, regression, and measurement and control. Topics cover analytical goals for assay precision, estimating the error variance components, indirect structural assays, functional assays, bivariate regression model, and least-squares estimates of the functional relation parameters. The manuscript takes a look at assay method comparison studies, multivariate analysis, forecasting and control, and test interpretation. Concerns include time series structure and terminology, polynomial regression, assessing the performance of the classification rule, quantitative screening tests, sample correlation coefficient, and computer assisted diagnosis. The book is a dependable reference for medical experts and statisticians interested in the employment of statistics in laboratory medicine.



Statistical Methods for Health Care Research

Statistical Methods for Health Care Research Author Barbara Hazard Munro
ISBN-10 0781748402
Release 2005
Pages 494
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Focusing on the statistical methods most frequently used in the health care literature and featuring numerous charts, graphs, and up-to-date examples from the literature, this text provides a thorough foundation for the statistics portion of nursing and all health care research courses. All Fifth Edition chapters include new examples and new computer printouts using the latest software, SPSS for Windows, Version 12. New material on regression diagnostics has been added.



Statistics in Medicine

Statistics in Medicine Author Robert H. Riffenburgh
ISBN-10 9780123848659
Release 2012-08-13
Pages 738
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Statistics in Medicine, Third Edition makes medical statistics easy to understand by students, practicing physicians, and researchers. The book begins with databases from clinical medicine and uses such data to give multiple worked-out illustrations of every method. The text opens with how to plan studies from conception to publication and what to do with your data, and follows with step-by-step instructions for biostatistical methods from the simplest levels (averages, bar charts) progressively to the more sophisticated methods now being seen in medical articles (multiple regression, noninferiority testing). Examples are given from almost every medical specialty and from dentistry, nursing, pharmacy, and health care management. A preliminary guide is given to tailor sections of the text to various lengths of biostatistical courses. User-friendly format includes medical examples, step-by-step methods, and check-yourself exercises appealing to readers with little or no statistical background, across medical and biomedical disciplines Facilitates stand-alone methods rather than a required sequence of reading and references to prior text Covers trial randomization, treatment ethics in medical research, imputation of missing data, evidence-based medical decisions, how to interpret medical articles, noninferiority testing, meta-analysis, screening number needed to treat, and epidemiology Fills the gap left in all other medical statistics books between the reader’s knowledge of how to go about research and the book’s coverage of how to analyze results of that research New in this Edition: New chapters on planning research, managing data and analysis, Bayesian statistics, measuring association and agreement, and questionnaires and surveys New sections on what tests and descriptive statistics to choose, false discovery rate, interim analysis, bootstrapping, Bland-Altman plots, Markov chain Monte Carlo (MCMC), and Deming regression Expanded coverage on probability, statistical methods and tests relatively new to medical research, ROC curves, experimental design, and survival analysis 35 Databases in Excel format used in the book and can be downloaded and transferred into whatever format is needed along with PowerPoint slides of figures, tables, and graphs from the book included on the companion site, http://www.elsevierdirect.com/companion.jsp?ISBN=9780123848642 Medical subject index offers additional search capabilities



Statistical Methods in Healthcare

Statistical Methods in Healthcare Author Frederick Faltin
ISBN-10 9781119942047
Release 2012-07-24
Pages 520
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In recent years the number of innovative medicinal products and devices submitted and approved by regulatory bodies has declined dramatically. The medical product development process is no longer able to keep pace with increasing technologies, science and innovations and the goal is to develop new scientific and technical tools and to make product development processes more efficient and effective. Statistical Methods in Healthcare focuses on the application of statistical methodologies to evaluate promising alternatives and to optimize the performance and demonstrate the effectiveness of those that warrant pursuit is critical to success. Statistical methods used in planning, delivering and monitoring health care, as well as selected statistical aspects of the development and/or production of pharmaceuticals and medical devices are also addressed. With a focus on finding solutions to these challenges, this book: Provides a comprehensive, in-depth treatment of statistical methods in healthcare, along with a reference source for practitioners and specialists in health care and drug development. Offers a broad coverage of standards and established methods through leading edge techniques. Uses an integrated, case-study based approach, with focus on applications. Looks at the use of analytical and monitoring schemes to evaluate therapeutic performance. Features the application of modern quality management systems to clinical practice, and to pharmaceutical development and production processes. Addresses the use of modern Statistical methods such as Adaptive Design, Seamless Design, Data Mining, Bayesian networks and Bootstrapping that can be applied to support the challenging new vision. Practitioners in healthcare-related professions, ranging from clinical trials to care delivery to medical device design, as well as statistical researchers in the field, will benefit from this book.



Introduction to Statistical Methods for Clinical Trials

Introduction to Statistical Methods for Clinical Trials Author Thomas D. Cook
ISBN-10 9781584880271
Release 2007-11-19
Pages 464
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Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials.