Introduction To Statistical Methods In Pathology
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| Author | : Amir Momeni |
| Publisher | : Springer |
| Total Pages | : 322 |
| Release | : 2017-09-07 |
| Genre | : Medical |
| ISBN | : 3319605437 |
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 | : Danny A. Milner, Jr., MD |
| Publisher | : Springer Publishing Company |
| Total Pages | : 207 |
| Release | : 2016-12-28 |
| Genre | : Medical |
| ISBN | : 161705268X |
This essential guide provides a clear, accessible review of the use of statistics in pathology studies. Spanning topics such as exploratory data analysis and descriptive statistics as well as the use of comparative statistics, concordance analysis, categorical and continuous data regression analyses, count data, survival analyses, decision point and clustering analysis, and more, this practical book comprehensively demystifies all the statistical knowledge paramount to working in the field. Throughout the guide, the author team highlights common errors and pitfalls that occur when performing tests and when interpreting data and make suggestions for how to avoid mistakes. Chapters are uniformly structured for ease of use and each chapter concludes with reviewquestions to facilitate self-assessment of the reader's skill in use of statistical methods. Statistics for Pathologists teaches trainees, junior investigators, and seasoned pathologists how to look at their data from the point of view of a statistician and determine what tests should be done, how the data and test should be presented, and how to use the tests practically. Learning statistical applications can greatly enhance and simplify the skills necessary to review and present data accurately and this basic understanding of statistics is critical in pathology-related work. Key Features Clear, concise overviews of every relevant statistical test with application in pathology-related research Includes real published studies to provide examples of use of the tests and interpretation of data Emphasizes how to avoid common errors and pitfalls when conducting tests and interpreting data Provides self-assessment review questions and answers in each chapter Comes with downloadable datasets for the reader so that they can perform statistical analysis tied to the book with popular stats programs
| Author | : Charan Singh Rayat |
| Publisher | : Springer |
| Total Pages | : 165 |
| Release | : 2018-08-23 |
| Genre | : Medical |
| ISBN | : 9811308276 |
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.
| Author | : Editor IJSMI |
| Publisher | : International Journal of Statistics and Medical Informatics |
| Total Pages | : 118 |
| Release | : 2020-03-23 |
| Genre | : Mathematics |
| ISBN | : |
Statistical Methods are widely used in Medical, Biological, Clinical, Business and Engineering field. The data which form the basis for the statistical methods helps us to take scientific and informed decisions. Statistical methods deal with the collection, compilation, analysis and making inference from the data. Statistical knowledge is also essential for the emerging field such as Machine Learning, Deep Learning and Artificial intelligence. This book deals with the statistical methods such as Probability, Sampling, Correlation, Regression and Hypothesis Testing and non-parametric tests and advanced statistical models. Examples discussed in the book are from different areas such as clinical, financial and marketing. The book uses open source R statistical software to carry out different statistical analysis with sample datasets. This book is third in series of Statistics books by the Author. Some of the contents are adopted from the author’s previous statistical books: Essentials of Biostatistics an overview with the help of software (ISBN-97817237120740) Editor International Journal of Statistics and Medical Informatics www.ijsmi.com/book.php www.amazon.com/dp/B0868TWQ6M- e-Book
| Author | : Robert F. Woolson |
| Publisher | : John Wiley & Sons |
| Total Pages | : 714 |
| Release | : 2011-01-25 |
| Genre | : Medical |
| ISBN | : 111803130X |
Dieser Band behandelt eine Reihe statistischer Themen, die bei der Analyse biologischer und medizinischer Daten allgemein Anwendung finden. Diese 2. Auflage wurde komplett überarbeitet, aktualisiert und erweitert. Einige Kapitel sind neu hinzugekommen, u.a. zur multiplen linearen Regression in der biomedizinischen Forschung. Der Stoff ist so gegliedert, dass der Leser den Text unabhängig von der jeweiligen statistischen Methode leicht nach Problemstellungen durchsuchen kann. Mit zahlreichen durchgearbeiteten Beispielen, die detaillierte Lösungsangaben zu Problemen aus der Praxis liefern.
| Author | : Z. Govindarajulu |
| Publisher | : Karger Medical and Scientific Publishers |
| Total Pages | : 249 |
| Release | : 2001 |
| Genre | : Science |
| ISBN | : 3805571194 |
In the face of the ever-increasing importance of statistical methods in medical research and practice, the first edition of this publication has provided a sound and deep understanding of statistical methods in bioassay to many students and researchers. In addition to the profound presentation of statistical methods of the first edition, here the reader will find new material stemming from the recent statistical literature as well as data reflecting modern trends in general applied statistical research. Examples are discussions on design and planning, e.g. choices of dose levels, and additional section in the chapter on Bayes methods, and a new chapter on sequential estimation for the logistic model. The book will be a valuable source of information to students in the experimental area of statistical aspects of biological assay, professional statisticians with an interest in research in this topic, teachers in statistics and biology, and investigators in the biological and medical sciences who use bioassay in their work.
| Author | : Xiao-Hua Zhou |
| Publisher | : John Wiley & Sons |
| Total Pages | : 597 |
| Release | : 2014-08-21 |
| Genre | : Medical |
| ISBN | : 1118626044 |
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.
| Author | : Anastasios A. Tsiatis |
| Publisher | : CRC Press |
| Total Pages | : 602 |
| Release | : 2019-12-19 |
| Genre | : Mathematics |
| ISBN | : 1498769780 |
Dynamic Treatment Regimes: Statistical Methods for Precision Medicine provides a comprehensive introduction to statistical methodology for the evaluation and discovery of dynamic treatment regimes from data. Researchers and graduate students in statistics, data science, and related quantitative disciplines with a background in probability and statistical inference and popular statistical modeling techniques will be prepared for further study of this rapidly evolving field. A dynamic treatment regime is a set of sequential decision rules, each corresponding to a key decision point in a disease or disorder process, where each rule takes as input patient information and returns the treatment option he or she should receive. Thus, a treatment regime formalizes how a clinician synthesizes patient information and selects treatments in practice. Treatment regimes are of obvious relevance to precision medicine, which involves tailoring treatment selection to patient characteristics in an evidence-based way. Of critical importance to precision medicine is estimation of an optimal treatment regime, one that, if used to select treatments for the patient population, would lead to the most beneficial outcome on average. Key methods for estimation of an optimal treatment regime from data are motivated and described in detail. A dedicated companion website presents full accounts of application of the methods using a comprehensive R package developed by the authors. The authors’ website www.dtr-book.com includes updates, corrections, new papers, and links to useful websites.
| Author | : P. W. Strike |
| Publisher | : Butterworth-Heinemann |
| Total Pages | : 553 |
| Release | : 2014-05-16 |
| Genre | : Medical |
| ISBN | : 1483161927 |
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.
| Author | : Martin Bland |
| Publisher | : Oxford University Press |
| Total Pages | : |
| Release | : 2015-07-23 |
| Genre | : Medical |
| ISBN | : 0192518399 |
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.
