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| who developed the concept of medical statistics: Medical Statistics Made Easy Michael Harris, Gordon Taylor, 2003-12-05 It is not necessary to know how to do a statistical analysis to critically appraise a paper. However, it is necessary to have a grasp of the basics, of whether the right test has been used and how to interpret the resulting figures. Short, readable, and useful, this book provides the essential, basic information without becoming bogged down in the |
| who developed the concept of medical statistics: The Road to Medical Statistics Eileen Magnello, Anne Hardy, 2002 There has been a growing recognition of the importance of mathematical and statistical methods in the history of medicine, particularly in those areas where statistical methods are a sine qua non such as epidemiology and randomised clinical trials. Despite this expanding scholarly interest, the development of the mathematical and statistical technologies in the biological sciences has not been examined systematically. This collection of essays aims to provide a broader overview of this field, and to explore the use of these with the use of these quantitative technologies in medical and clinical cultures from the seventeenth to the twentieth centuries. |
| who developed the concept of medical statistics: Principles of Medical Statistics Austin Bradford Hill, 1949 |
| who developed the concept of medical statistics: Medical Statistics Made Easy 2e - now superseded by 3e M. Harris, G. Taylor, 2008-02-29 This new edition of Medical Statistics Made Easy 2nd edition enables readers to understand the key statistical techniques used throughout the medical literature. Featuring a comprehensive updating of the 'Statistics at work' section, this new edition retains a consistent, concise, and user-friendly format. Each technique is graded for ease of use and frequency of appearance in the mainstream medical journals. Medical Statistics Made Easy 2nd edition is essential reading for anyone looking to understand: * confidence intervals and probability values * numbers needed to treat * t tests and other parametric tests * survival analysis If you need to understand the medical literature, then you need to read this book. Reviews: This book helps medical students understand the basic concepts of medical statistics starting in a 'step-by-step approach'. The authors have designed the book assuming that the reader has no prior knowledge. It focuses on the most common statistical concepts that are likely to be faced in medical literature. All chapters are concise and simple to understand. Each chapter starts with an introduction which consists of “how important” that particular statistical concept is, using a 'star' system. A 'thumbs-up' system shows how easy the statistical concept is to understand. Both these systems indicate time-efficient learning allowing yourself to focus on areas you find most difficult. Following this, there are worked out examples with exam-tips at the end of some chapters. The last chapter, 'Statistics at Work', shows how medical statistics is put into practice using worked out examples from renowned journals. This helps in assessing the reader’s own knowledge and gives them confidence in analysis of statistics of a journal. In conclusion, we would recommend this book as an introduction into medical statistics before plunging into the deep 'statistical' waters! It gives confidence to the reader in taking up the challenge of understanding statistics and [being] able to apply knowledge in analysing medical literature. Stefanie Zhao Lin Lip & Louise Murchison, Scottish Medical Journal, June 2010 If ever there was a book that completely lived up to its title, this is it...Perhaps above everything, it is the chapter layout and design that makes this book stand out head and shoulders above the crowd. At the beginning of each chapter two questions are posed – how important is the subject in question and how difficult is it to understand? The first is answered on the basis of how often the subject is mentioned / used in papers published in mainstream medical journals. A star rating is then given from one to five with five stars implying use in the majority of papers published. The second question is answered by means of a ‘thumbs up’ grading system. The more thumbs, the easier the concept is to understand (maximum of five). This, of course, provides a route into statistics for even the most idle of uneducated individuals! Five stars and five thumbs must surely indicate time-efficient learning! At the end of each chapter exam tips (light bulb icon!) are given – I doubt anyone could ask for more! The whole way in which the authors have written this book is commendable; the chapters are succinct, easy to follow and a pleasure to read...Is it value for money? – a definite yes even at twice the price. Of course I never exaggerate but if you breathe, you should own this book! Ian Pearce, Urology News, June 2010 |
| who developed the concept of medical statistics: Oxford Handbook of Medical Statistics Janet Peacock, Philip Peacock, 2011 The majority of medical research involves quantitative methods and so it is essential to be able to understand and interpret statistics. This book shows readers how to develop the skills required to critically appraise research evidence effectively, and how to conduct research and communicate their findings. |
| who developed the concept of medical statistics: Using and Understanding Medical Statistics David E. Matthews, Vernon T. Farewell, 1985 Since the last edition of this book was published, major developments in computer technology have affected both the practice of medicine and the methods of analyzing medical data. These advances make the focus of this revised edition - understanding many of the statistical methods that are used in modern medical studies-all the more important. Two new chapters have been added by the authors. One provides readers with an introduction to the analysis of longitudinal data. The other augments previous material concerning the design of clinical trials, exploring topics such as the use of surrogate markers, multiple outcomes, equivalence trials, and the planning of efficacy-toxicity studies. In addition to providing new information and fine-tuning the rest of the book, the authors have reorganized the final six chapters so that the topics build, naturally, on each other. This latest edition is highly recommended both as an excellent introduction to medical statistics and as a valuable tool in explaining the more complex statistical methods and techniques used today. |
| who developed the concept of medical statistics: An Introduction to Medical Statistics Martin Bland, 2015-07-23 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. |
| who developed the concept of medical statistics: Making Sense of Medical Statistics Munier Hossain, 2021-10-21 Do you want to know what a parametric test is and when not to perform one? Do you get confused between odds ratios and relative risks? Want to understand the difference between sensitivity and specificity? Would like to find out what the fuss is about Bayes' theorem? Then this book is for you! Physicians need to understand the principles behind medical statistics. They don't need to learn the formula. The software knows it already! This book explains the fundamental concepts of medical statistics so that the learner will become confident in performing the most commonly used statistical tests. Each chapter is rich in anecdotes, illustrations, questions, and answers. Not enough? There is more material online with links to free statistical software, webpages, multimedia content, a practice dataset to get hands-on with data analysis, and a Single Best Answer questionnaire for the exam. |
| who developed the concept of medical statistics: Statistics in Medicine Robert H. Riffenburgh, Daniel L. Gillen, 2020-07-03 Statistics in Medicine, Fourth Edition, helps medical and biomedical investigators design and answer questions about analyzing and interpreting data and predicting the sample size required to achieve useful results. It makes medical statistics easy for the non-biostatistician by outlining common methods used in 90% of medical research. The text covers how to plan studies from conception to publication, what to do with data, and follows with step-by-step instructions for biostatistical methods from the simplest levels, to more sophisticated methods now used in medical articles. Examples from almost every medical specialty, and from dentistry, nursing, pharmacy and health care management are provided. This book does not require background knowledge of statistics or mathematics beyond high school algebra and provides abundant clinical examples and exercises to reinforce concepts. It is a valuable source for biomedical researchers, healthcare providers and anyone who conducts research or quality improvement projects. - Expands and revises important topics, such as basic concepts behind descriptive statistics and testing, descriptive statistics in three dimensions, the relationship between statistical testing and confidence intervals, and more - Presents an easy-to-follow format with medical examples, step-by-step methods and check-yourself exercises - Explains statistics for users with little statistical and mathematical background - Encompasses all research development stages, from conceiving a study, planning it in detail, carrying out the methods, putting obtained data in analyzable form, analyzing and interpreting the results, and publishing the study |
| who developed the concept of medical statistics: Medical Statistics Michael J. Campbell, David Machin, Stephen J. Walters, 2010-10-26 Provides students and practitioners with a clear, conciseintroduction to the statistics they will come across in theirregular reading of clinical papers. Written by three experts with wide teaching and consultingexperience, Medical Statistics: A Textbook for the HealthSciences, Fourth Edition: Assumes no prior knowledge of statistics Covers all essential statistical methods Completely revised, updated and expanded Includes numerous examples and exercises on the interpretationof the statistics in papers published in medical journals From the reviews of the previous edition: The book has several excellent features: it is written bystatisticians, is.... well presented, is well referenced.... and isshort. THE LANCET Many statisticians are concerned at the generally poorstandard of statistics in papers published in medical journals.Perhaps this could be remedied if more research workers would sparea few hours to read through Campbell and Machin's book.BRITISH MEDICAL JOURNAL ... a simple, interesting and insightful introduction tomedical statistics... highlyrecommended. STATISTICAL METHODS IN MEDICALRESEARCH Campbell and Machin found the golden mean... this book canbe recommended for all students and all medicalresearchers. ISCB NEWSLETTER |
| who developed the concept of medical statistics: Medical Statistics Stephen J. Walters, Michael J. Campbell, David Machin, 2021-02-01 The 5th Edition of this popular introduction to statistics for the medical and health sciences has undergone a significant revision, with several new chapters added and examples refreshed throughout the book. Yet it retains its central philosophy to explain medical statistics with as little technical detail as possible, making it accessible to a wide audience. Helpful multi-choice exercises are included at the end of each chapter, with answers provided at the end of the book. Each analysis technique is carefully explained and the mathematics kept to minimum. Written in a style suitable for statisticians and clinicians alike, this edition features many real and original examples, taken from the authors' combined many years' experience of designing and analysing clinical trials and teaching statistics. Students of the health sciences, such as medicine, nursing, dentistry, physiotherapy, occupational therapy, and radiography should find the book useful, with examples relevant to their disciplines. The aim of training courses in medical statistics pertinent to these areas is not to turn the students into medical statisticians but rather to help them interpret the published scientific literature and appreciate how to design studies and analyse data arising from their own projects. However, the reader who is about to design their own study and collect, analyse and report on their own data will benefit from a clearly written book on the subject which provides practical guidance to such issues. The practical guidance provided by this book will be of use to professionals working in and/or managing clinical trials, in academic, public health, government and industry settings, particularly medical statisticians, clinicians, trial co-ordinators. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations. |
| who developed the concept of medical statistics: Advanced Medical Statistics (2nd Edition) Ying Lu, Ji-qian Fang, Lu Tian, Hua Jin, 2015-06-29 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. |
| who developed the concept of medical statistics: Principles of Medical Statistics Alvan R. Feinstein, 2001-09-14 The get-it-over-with-quickly approach to statistics has been encouraged - and often necessitated - by the short time allotted to it in most curriculums. If included at all, statistics is presented briefly, as a task to be endured mainly because pertinent questions may appear in subsequent examinations for licensure or other certifications. However, |
| who developed the concept of medical statistics: Medical Statistics Jennifer Peat, Belinda Barton, 2008-04-15 Holistic approach to understanding medical statistics This hands-on guide is much more than a basic medical statistics introduction. It equips you with the statistical tools required for evidence-based clinical research. Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs. Showing you how to: analyse data with the help of data set examples (Click here to download datasets) select the correct statistics and report results for publication or presentation understand and critically appraise results reported in the literature Each statistical test is linked to the research question and the type of study design used. There are also checklists for critically appraising the literature and web links to useful internet sites. Clear and concise explanations, combined with plenty of examples and tabulated explanations are based on the authors’ popular medical statistics courses. Critical appraisal guidelines at the end of each chapter help the reader evaluate the statistical data in their particular contexts. |
| who developed the concept of medical statistics: Essential Statistical Methods for Medical Statistics J. Philip Miller, 2010-11-08 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 |
| who developed the concept of medical statistics: Medical Statistics at a Glance Aviva Petrie, Caroline Sabin, 2019-09-30 Now in its fourth edition, Medical Statistics at a Glance is a concise and accessible introduction to this complex subject. It provides clear instruction on how to apply commonly used statistical procedures in an easy-to-read, comprehensive and relevant volume. This new edition continues to be the ideal introductory manual and reference guide to medical statistics, an invaluable companion for statistics lectures and a very useful revision aid. This new edition of Medical Statistics at a Glance: Offers guidance on the practical application of statistical methods in conducting research and presenting results Explains the underlying concepts of medical statistics and presents the key facts without being unduly mathematical Contains succinct self-contained chapters, each with one or more examples, many of them new, to illustrate the use of the methodology described in the chapter. Now provides templates for critical appraisal, checklists for the reporting of randomized controlled trials and observational studies and references to the EQUATOR guidelines for the presentation of study results for many other types of study Includes extensive cross-referencing, flowcharts to aid the choice of appropriate tests, learning objectives for each chapter, a glossary of terms and a glossary of annotated full computer output relevant to the examples in the text Provides cross-referencing to the multiple choice and structured questions in the companion Medical Statistics at a Glance Workbook Medical Statistics at a Glance is a must-have text for undergraduate and post-graduate medical students, medical researchers and biomedical and pharmaceutical professionals. |
| who developed the concept of medical statistics: Medical Statistics at a Glance Workbook Aviva Petrie, Caroline Sabin, 2012-12-13 This comprehensive workbook contains a variety of self-assessment methods that allow readers to test their statistical knowledge, put it into practice, and apply it in a medical context, while also providing guidance when critically appraising published literature. It is designed to support the best-selling third edition of Medical Statistics at a Glance, to which it is fully cross-referenced, but may be used independently of it. Ideal for medical students, junior doctors, researchers and anyone working in the biomedical and pharmaceutical disciplines who wants to feel more confident in basic medical statistics, the title includes: Over 80 MCQs, each testing knowledge of a single statistical concept or aspect of study interpretation 29 structured questions to explore in greater depth several statistical techniques or principles, including the choice of appropriate statistical analyses and the interpretation of study findings Templates for the appraisal of clinical trials and observational studies, plus full appraisals of two published papers to demonstrate the use of these templates in practice Detailed step-by-step analyses of two substantial data sets (also available at www.medstatsaag.com) to demonstrate the application of statistical procedures to real-life research Medical Statistics at a Glance Workbook is the ideal resource to test statistical knowledge and improve analytical and interpretational skills. Additional resources are available at www.medstatsaag.com, including: Excel datasets to accompany the data analysis section Downloadable PDFs of two templates for critical appraisal Links to online further reading Supplementary MCQs |
| who developed the concept of medical statistics: Practical Statistics for Medical Research Douglas G. Altman, 1990-11-22 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. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research. |
| who developed the concept of medical statistics: Principles of Medical Statistics Austin Bradford Hill, 1971 |
| who developed the concept of medical statistics: Epidemiology and Medical Statistics , 2007-11-21 This volume, representing a compilation of authoritative reviews on a multitude of uses of statistics in epidemiology and medical statistics written by internationally renowned experts, is addressed to statisticians working in biomedical and epidemiological fields who use statistical and quantitative methods in their work. While the use of statistics in these fields has a long and rich history, explosive growth of science in general and clinical and epidemiological sciences in particular have gone through a see of change, spawning the development of new methods and innovative adaptations of standard methods. Since the literature is highly scattered, the Editors have undertaken this humble exercise to document a representative collection of topics of broad interest to diverse users. The volume spans a cross section of standard topics oriented toward users in the current evolving field, as well as special topics in much need which have more recent origins. This volume was prepared especially keeping the applied statisticians in mind, emphasizing applications-oriented methods and techniques, including references to appropriate software when relevant.· 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 |
| who developed the concept of medical statistics: Medical Statistics at a Glance Aviva Petrie, Caroline Sabin, 2000-08-16 In line with the other books in the at a Glance series, Medical Statistics at a Glance leads the reader through a number of self-contained topics, each covering a different aspect of medical statistics. The majority of these use the standard 'At a Glance' format of two pages per topic. The authors have provided a basic introduction to the underlying concepts of medical statistics and a guide to the most commonly used statistical procedures. Topics describing a statistical technique are accompanied by a worked example, using real data, illustrating its use. Where possible, the same data set has been used in more than one topic to reflect the reality of data analysis. Detailed and complex hand calculations have been avoided with a concentration on the interpretation of computer data analysis. Medical Statistics at a Glance is versatile in its use as an explanation, a revision summary and a long-term source of reference. Worked examples to accompany each topic. Emphasis on computer analysis of data rather than hand calculations. Supported by a website at http://www.medstatsaag.com/ - this site contains useful self-assessment questions to aid student learning. |
| who developed the concept of medical statistics: Modern Medical Statistics Brian S. Everitt, 2010-06-28 Statistical science plays an increasingly important role in medical research. Over the last few decades, many new statistical methods have been developed which have particular relevance for medical researchers and, with the appropriate software now easily available, these techniques can be used almost routinely to great effect. These innovative methods include survival analysis, generalized additive models and Bayesian methods. Modern Medical Statistics covers these essential new techniques at an accessible technical level, its main focus being not on the theory but on the effective practical application of these methods in medical research. Modern Medical Statistics is an indispensable practical guide for medical researchers and medical statisticians as well as an ideal text for advanced courses in medical statistics and public health. |
| who developed the concept of medical statistics: Introductory Medical Statistics, 3rd edition Richard F. Mould, 1998-01-01 Introductory Medical Statistics, now in its third edition, is an introductory textbook on basic statistical techniques. It is written for physicians, surgeons, radiation oncologists, medical physicists, radiographers, hospital administrators, medical statisticians in training, biochemists, and other professionals allied to medicine. It is suitable |
| who developed the concept of medical statistics: Toward a National Health Care Survey National Research Council, Division of Behavioral and Social Sciences and Education, Institute of Medicine, Commission on Behavioral and Social Sciences and Education, Committee on National Statistics, Division of Health Care Services, Panel on the National Health Care Survey, 1992-02-01 The nation's health care system has changed dramatically and the country is debating further significant changes. Comprehensive information is needed to guide policymakers in understanding and evaluating the current problems and in formulating federal health care policy. This book contains an evaluation of the plan developed by the National Center for Health Statistics for restructuring its existing provider surveys. It identifies current and future data needed by researchers and policymakers to assess the effect of changes in financing, organization, and delivery of health care on access, quality, costs, and outcomes of care and determines the extent to which the design and content of the proposed survey can meet these data needs. The book goes beyond a simple review and recommends a design framework to develop a coordinated and integrated data system to gather information about people and their illness over time and to link this information to costs and health care outcomes. |
| who developed the concept of medical statistics: Statistics for Health Care Professionals Ian Scott, Debbie Mazhindu, 2005-02-09 Focusing on quantative approaches to investigating problems, this title introduces the basics rules and principles of statistics, encouraging the reader to think critically about data analysis and research design, and how these factors can impact upon evidence-based practice. |
| who developed the concept of medical statistics: The Future of Public Health Committee for the Study of the Future of Public Health, Division of Health Care Services, Institute of Medicine, 1988-01-15 The Nation has lost sight of its public health goals and has allowed the system of public health to fall into 'disarray', from The Future of Public Health. This startling book contains proposals for ensuring that public health service programs are efficient and effective enough to deal not only with the topics of today, but also with those of tomorrow. In addition, the authors make recommendations for core functions in public health assessment, policy development, and service assurances, and identify the level of government--federal, state, and local--at which these functions would best be handled. |
| who developed the concept of medical statistics: Statistical Issues in Drug Development Stephen S. Senn, 2008-02-28 Drug development is the process of finding and producingtherapeutically useful pharmaceuticals, turning them into safe andeffective medicine, and producing reliable information regardingthe appropriate dosage and dosing intervals. With regulatoryauthorities demanding increasingly higher standards in suchdevelopments, statistics has become an intrinsic and criticalelement in the design and conduct of drug development programmes. Statistical Issues in Drug Development presents anessential and thought provoking guide to the statistical issues andcontroversies involved in drug development. This highly readable second edition has been updated toinclude: Comprehensive coverage of the design and interpretation ofclinical trials. Expanded sections on missing data, equivalence, meta-analysisand dose finding. An examination of both Bayesian and frequentist methods. A new chapter on pharmacogenomics and expanded coverage ofpharmaco-epidemiology and pharmaco-economics. Coverage of the ICH guidelines, in particular ICH E9,Statistical Principles for Clinical Trials. It is hoped that the book will stimulate dialogue betweenstatisticians and life scientists working within the pharmaceuticalindustry. The accessible and wide-ranging coverage make itessential reading for both statisticians and non-statisticiansworking in the pharmaceutical industry, regulatory bodies andmedical research institutes. There is also much to benefitundergraduate and postgraduate students whose courses include amedical statistics component. |
| who developed the concept of medical statistics: Statistics in the Health Sciences Albert Vexler, Alan Hutson, 2018-01-19 This very informative book introduces classical and novel statistical methods that can be used by theoretical and applied biostatisticians to develop efficient solutions for real-world problems encountered in clinical trials and epidemiological studies. The authors provide a detailed discussion of methodological and applied issues in parametric, semi-parametric and nonparametric approaches, including computationally extensive data-driven techniques, such as empirical likelihood, sequential procedures, and bootstrap methods. Many of these techniques are implemented using popular software such as R and SAS.— Vlad Dragalin, Professor, Johnson and Johnson, Spring House, PA It is always a pleasure to come across a new book that covers nearly all facets of a branch of science one thought was so broad, so diverse, and so dynamic that no single book could possibly hope to capture all of the fundamentals as well as directions of the field. The topics within the book’s purview—fundamentals of measure-theoretic probability; parametric and non-parametric statistical inference; central limit theorems; basics of martingale theory; Monte Carlo methods; sequential analysis; sequential change-point detection—are all covered with inspiring clarity and precision. The authors are also very thorough and avail themselves of the most recent scholarship. They provide a detailed account of the state of the art, and bring together results that were previously scattered across disparate disciplines. This makes the book more than just a textbook: it is a panoramic companion to the field of Biostatistics. The book is self-contained, and the concise but careful exposition of material makes it accessible to a wide audience. This is appealing to graduate students interested in getting into the field, and also to professors looking to design a course on the subject. — Aleksey S. Polunchenko, Department of Mathematical Sciences, State University of New York at Binghamton This book should be appropriate for use both as a text and as a reference. This book delivers a ready-to-go well-structured product to be employed in developing advanced courses. In this book the readers can find classical and new theoretical methods, open problems and new procedures. The book presents biostatistical results that are novel to the current set of books on the market and results that are even new with respect to the modern scientific literature. Several of these results can be found only in this book. |
| who developed the concept of medical statistics: Biostatistics Wayne W. Daniel, Chad L. Cross, 2018-11-13 The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference. |
| who developed the concept of medical statistics: Presenting Medical Statistics from Proposal to Publication Janet L. Peacock, Sally M. Kerry, Raymond R. Balise, 2017-07-21 As many medical and healthcare researchers have a love-hate relationship with statistics, the second edition of this practical reference book may make all the difference. Using practical examples, mainly from the authors' own research, the book explains how to make sense of statistics, turn statistical computer output into coherent information, and help decide which pieces of information to report and how to present them. The book takes you through all the stages of the research process, from the initial research proposal, through ethical approval and data analysis, to reporting on and publishing the findings. Helpful tips and information boxes, offer clear guidance throughout, including easily followed instructions on how to: -develop a quantitative research proposal for ethical/institutional approval or research funding -write up the statistical aspects of a paper for publication -choose and perform simple and more advanced statistical analyses -describe the statistical methods and present the results of an analysis. This new edition covers a wider range of statistical programs - SAS, STATA, R, and SPSS, and shows the commands needed to obtain the analyses and how to present it, whichever program you are using. Each specific example is annotated to indicate other scenarios that can be analysed using the same methods, allowing you to easily transpose the knowledge gained from the book to your own research. The principles of good presentation are also covered in detail, from translating relevant results into suitable extracts, through to randomised controlled trials, and how to present a meta-analysis. An added ingredient is the inclusion of code and datasets for all analyses shown in the book on our website (http://medical-statistics.info). Written by three experienced biostatisticians based in the UK and US, this is a step-by-step guide that will be invaluable to researchers and postgraduate students in medicine, those working in the professions allied to medicine, and statisticians in consultancy roles. |
| who developed the concept of medical statistics: Applied Medical Statistics Using SAS Geoff Der, Brian S. Everitt, 2012-10-01 Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudi |
| who developed the concept of medical statistics: Dicing with Death Stephen Senn, 2003-11-20 If you think that statistics has nothing to say about what you do or how you could do it better, then you are either wrong or in need of a more interesting job. Stephen Senn explains here how statistics determines many decisions about medical care, from allocating resources for health, to determining which drugs to license, to cause-and-effect in relation to disease. He tackles big themes: clinical trials and the development of medicines, life tables, vaccines and their risks or lack of them, smoking and lung cancer and even the power of prayer. He entertains with puzzles and paradoxes and covers the lives of famous statistical pioneers. By the end of the book the reader will see how reasoning with probability is essential to making rational decisions in medicine, and how and when it can guide us when faced with choices that impact on our health and even life. |
| who developed the concept of medical statistics: Encyclopaedic Companion to Medical Statistics Brian S. Everitt, Christopher R. Palmer, 2011-06-20 Statistical methodology is of great importance to medical research and clinical practice. The Encyclopaedic Companion to Medical Statistics contains readable accounts of the key topics central to current research and practice. Each entry has been written by an individual chosen for both their expertise in the field and their ability to communicate statistical concepts successfully to medical researchers. Real examples from the biomedical literature and relevant illustrations feature in many entries and extensive cross–referencing signposts the reader to related entries. Key Features: Contains accounts of over 400 statistical topics central to current medical research. 80% of first edition entries updated and revised. Presents the latest techniques used at the cutting edge of medical research. Covers common errors in statistical analyses in medicine. Real examples from the biomedical literature and relevant illustrations feature throughout. Contains contributions from over 70 experts in the field. Medical researchers, researchers and practitioners in medical research and statistics will benefit greatly from this book. |
| who developed the concept of medical statistics: Essential Medical Statistics Betty Kirkwood, Jonathan Sterne, 2003-06-27 Blackwell Publishing is delighted to announce that this book has been Highly Commended in the 2004 BMA Medical Book Competition. Here is the judges' summary of this book: This is a technical book on a technical subject but presented in a delightful way. There are many books on statistics for doctors but there are few that are excellent and this is certainly one of them. Statistics is not an easy subject to teach or write about. The authors have succeeded in producing a book that is as good as it can get. For the keen student who does not want a book for mathematicians, this is an excellent first book on medical statistics. Essential Medical Statistics is a classic amongst medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that demystifies the subject, while providing a comprehensive coverage of advanced as well as basic methods. The second edition of Essential Medical Statistics has been comprehensively revised and updated to include modern statistical methods and modern approaches to statistical analysis, while retaining the approachable and non-mathematical style of the first edition. The book now includes full coverage of the most commonly used regression models, multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as a chapter on general issues in regression modelling. In addition, new chapters introduce more advanced topics such as meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data. Aimed at students of medical statistics, medical researchers, public health practitioners and practising clinicians using statistics in their daily work, the book is designed as both a teaching and a reference text. The format of the book is clear with highlighted formulae and worked examples, so that all concepts are presented in a simple, practical and easy-to-understand way. The second edition enhances the emphasis on choice of appropriate methods with new chapters on strategies for analysis and measures of association and impact. Essential Medical Statistics is supported by a web site at www.blackwellpublishing.com/essentialmedstats. This useful online resource provides statistical datasets to download, as well as sample chapters and future updates. |
| who developed the concept of medical statistics: Prognosis Research in Healthcare Richard D. Riley, Danielle van der Windt, Peter Croft, Karel G. M. Moons, 2019-01-17 What is going to happen to me? Most patients ask this question during a clinical encounter with a health professional. As well as learning what problem they have (diagnosis) and what needs to be done about it (treatment), patients want to know about their future health and wellbeing (prognosis). Prognosis research can provide answers to this question and satisfy the need for individuals to understand the possible outcomes of their condition, with and without treatment. Central to modern medical practise, the topic of prognosis is the basis of decision making in healthcare and policy development. It translates basic and clinical science into practical care for patients and populations. Prognosis Research in Healthcare: Concepts, Methods and Impact provides a comprehensive overview of the field of prognosis and prognosis research and gives a global perspective on how prognosis research and prognostic information can improve the outcomes of healthcare. It details how to design, carry out, analyse and report prognosis studies, and how prognostic information can be the basis for tailored, personalised healthcare. In particular, the book discusses how information about the characteristics of people, their health, and environment can be used to predict an individual's future health. Prognosis Research in Healthcare: Concepts, Methods and Impact, addresses all types of prognosis research and provides a practical step-by-step guide to undertaking and interpreting prognosis research studies, ideal for medical students, health researchers, healthcare professionals and methodologists, as well as for guideline and policy makers in healthcare wishing to learn more about the field of prognosis. |
| who developed the concept of medical statistics: Medical Statistics in World War II United States. Army Medical Department (1968- ), Frank A. Reister, 1976 |
| who developed the concept of medical statistics: How to Practice Academic Medicine and Publish from Developing Countries? Samiran Nundy, Atul Kakar, Zulfiqar A. Bhutta, 2021-10-23 This is an open access book. The book provides an overview of the state of research in developing countries – Africa, Latin America, and Asia (especially India) and why research and publications are important in these regions. It addresses budding but struggling academics in low and middle-income countries. It is written mainly by senior colleagues who have experienced and recognized the challenges with design, documentation, and publication of health research in the developing world. The book includes short chapters providing insight into planning research at the undergraduate or postgraduate level, issues related to research ethics, and conduct of clinical trials. It also serves as a guide towards establishing a research question and research methodology. It covers important concepts such as writing a paper, the submission process, dealing with rejection and revisions, and covers additional topics such as planning lectures and presentations. The book will be useful for graduates, postgraduates, teachers as well as physicians and practitioners all over the developing world who are interested in academic medicine and wish to do medical research. |
| who developed the concept of medical statistics: Strategy and Statistics in Clinical Trials Joseph Tal, 2011-07-14 Delineates the statistical building blocks and concepts of clinical trials. |
| who developed the concept of medical statistics: Survival and Event History Analysis Odd Aalen, Ornulf Borgan, Hakon Gjessing, 2008-09-16 The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully. The common denominator of such models is stochastic processes. The authors show how counting processes, martingales, and stochastic integrals fit very nicely with censored data. Beginning with standard analyses such as Kaplan-Meier plots and Cox regression, the presentation progresses to the additive hazard model and recurrent event data. Stochastic processes are also used as natural models for individual frailty; they allow sensible interpretations of a number of surprising artifacts seen in population data. The stochastic process framework is naturally connected to causality. The authors show how dynamic path analyses can incorporate many modern causality ideas in a framework that takes the time aspect seriously. To make the material accessible to the reader, a large number of practical examples, mainly from medicine, are developed in detail. Stochastic processes are introduced in an intuitive and non-technical manner. The book is aimed at investigators who use event history methods and want a better understanding of the statistical concepts. It is suitable as a textbook for graduate courses in statistics and biostatistics. |
| who developed the concept of medical statistics: Statistical Procedures for the Medical Device Industry Wayne A. Taylor, 2017 |
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Nov 24, 2010 · Love the Google fight thing! Presumably people get confused because a double consonant usually produces a short vowel sound, like …
to be develop/to be developed | WordReference Forums
Sep 18, 2006 · Absolutely not. In your examples, it only works without the word "be" ie. to develop, to …
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Nov 3, 2010 · To be a little bit more formal, I'd use the structure 'developed for + ing form.' Just as a tip: If you see on the net the combination …
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Jan 26, 2015 · Dear all There was an argue related to the meanings of the two verbs concerning the following point: One of " develop" meaning is : …
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Jul 1, 2018 · I developed/have developed an interest in machine learning over the course of my academic and professional career, …
developped / developed - WordReference Forums
Nov 24, 2010 · Love the Google fight thing! Presumably people get confused because a double consonant usually produces a short vowel sound, like 'loped' vs. 'lopped' or 'hoped' vs …
to be develop/to be developed | WordReference Forums
Sep 18, 2006 · Absolutely not. In your examples, it only works without the word "be" ie. to develop, to announce, etc.
developed to/for - WordReference Forums
Nov 3, 2010 · To be a little bit more formal, I'd use the structure 'developed for + ing form.' Just as a tip: If you see on the net the combination "developed for' you can see it appears around …
Create Vs Develop - WordReference Forums
Jan 26, 2015 · Dear all There was an argue related to the meanings of the two verbs concerning the following point: One of " develop" meaning is : to bring into being or activity; generate; …
developed vs have developed | WordReference Forums
Jul 1, 2018 · I developed/have developed an interest in machine learning over the course of my academic and professional career, and while consulting for multinational companies such as X …
has been developed / was developed | WordReference Forums
Apr 10, 2011 · Hi, is there any difference in meaning in the following context: [leaflet about a newly developed programme for IT specialists, first sentence] "Our programme has been / was …
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Mar 30, 2022 · Has developed doesn't preclude the idea of further development, but it doesn't emphasize the ongoing nature of the development. Has been developing emphasizes the …
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Sep 17, 2020 · Hi, I would like to ask you which of the options in bold is correct in the following (I would opt for the first): In the course of my academic and professional career, I have …
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Jan 15, 2009 · Nevertheless, the one who actually developed them was only my friend himself. I think the experience doesn't boost his teaching abilities, but it allows him to improve them. …
Synonym for "developed an interest" - WordReference Forums
Oct 6, 2012 · Hello, I am trying to find a synonym for the construction "I developed an interest in X because...". Is it okay to say something like this: "X holds my interest because..." ? If so, which …
