Interpreting statistical findings, Walker, Jan Almond, Palo
Автор: Willenborg Название: Statistical Disclosure Control in Practice ISBN: 0387947221 ISBN-13(EAN): 9780387947228 Издательство: Springer Рейтинг: Цена: 13584 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The aim of this book is to discuss various aspects associated with disseminating personal or business data collected in censuses or surveys or copied from
administrative sources. The problem is to present the data in such a form that they are useful for statistical research and to provide sufficient protection for the individuals or businesses
to whom the data refer. The major part of this book is concerned with how to define the disclosure problem and how to deal with it in practical circumstances.
Автор: Walker, Jan Almond, Palo Название: Interpreting statistical findings ISBN: 0335235964 ISBN-13(EAN): 9780335235964 Издательство: McGraw-Hill Рейтинг: Цена: 7508 р. Наличие на складе: Поставка под заказ.
Описание: This book is aimed at those studying and working in the field of health care, including nurses and the professions allied to medicine, who have little prior knowledge of statistics but for whom critical review of research is an essential skill.
Автор: Malley Название: Statistical Learning for Biomedical Data ISBN: 0521699096 ISBN-13(EAN): 9780521699099 Издательство: Cambridge Academ Рейтинг: Цена: 4025 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random Forests™, neural nets, support vector machines, nearest neighbors and boosting.
Автор: Savitz Название: Interpreting Epidemiologic Evidence ISBN: 019510840X ISBN-13(EAN): 9780195108408 Издательство: Oxford Academ Рейтинг: Цена: 4486 р. Наличие на складе: Поставка под заказ.
Описание: This book offers a strategy for assessing epidemiologic research findings. Specific tools for assessing the presence and impact of selection bias in both cohort and case-control studies, bias from non-response, confounding, exposure measurement error, disease measurement error, and random error are identified and evaluated.
Описание: As medical research becomes sophisticated, and as statistical analysis becomes more complex, keeping up with medical literature can seem challenging. This book enhances the reader`s ability to demystify, interpret, and analyze research literature.
Описание: Presents an overview of methods used for investigating the health effects of air pollution and gives examples and case studies in R which demonstrate the application of those methods to real data. The book is suitable for statisticians, epidemiologists, and graduate students working in the area of air pollution and health.
Описание: Reflects developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; accelerated life models; quality of life; and statistical challenges in genomics. This book is for researchers and practitioners in applied probability and statistics, industrial statistics and biostatistics.
Описание: Explains the principles and theory of statistical modelling for non-mathematical social scientists looking to apply statistical modelling techniques in research. This book offers guidance and instruction in fitting models using SPSS and Stata, statistical computer software which is available to most social researchers.
Описание: This volume contains refereed papers by participants in the two weeks on Clinical Trials and one week on Epidemiology and the Environment held as part of
the six weeks workshop on Statistics in the Health Sciences Applications at the Institute for Mathematics and its Applications (IMA) in the summer of 1997. Donald Berry was in charge
of the weeks on clinical trials, and Elizabeth Halloran organized the week on epidemiology and the environment. The collection includes a major contribution from Jamie Robins, Andrea
Rotnitzky, and Daniel Scharfstein on sensitivity analysis for selection bias and unmeasured confounding in missing data and causal and inference models.
In another paper,
Jamie Robins prese
ts a new class of causal models called marginal structural models. Alan Hubbard, Mark van der Laan, and Jamie Robins present a methodology for consistent and efficient estimation of
treatment-specific survival functions in observational settings. Brian Leroux, Xingye Lei, and Norman Breslow present a new mixed model for spatial dependence for estimating disease
rates in small areas.
Andrew Lawson and Allan Clark demonstrate Markov Chain Monte Carlo methods for clustering in spatial epidemiology. Colin Chen, David Chock, and
Sandra Winkler present a simulation study examining confounding in estimation of the epidemiologic effect of air pollution. Dalene Stangl discusses issues in the use of reference priors
and Bayes factors in analyzing clinical trials.
Stephen George reviews the role of surrogate endpoints in cancer clinical trials.
Описание: This text provides a clear discussion of the basic statistical concepts and methods frequently encountered in statistical research. Assuming only a basic level of Mathematics, and with numerous examples and illustrations, this text is a valuable resource for students and researchers in the Sciences and Social Sciences.
Описание: Lowers the Learning Curve for Physicians and Researchers!The successful Statistical Reasoning in Medicine: The Intuitive P-value Primer, with its novel emphasis on patient and community protection, illustrated the correct use of statistics in health care research for healthcare workers. Through clear explanations and examples, this book provided the non-mathematician with a foundation for understanding the underlying statistical reasoning process in clinical research, the core principles of research design, and the correct use of statistical inference and p-values.The P-Value Primer 2nd Edition levels the learning curve of statistics for health care researchers by further de-emphasizing mathematical and computational devices, bringing the principles of statistical reasoning closer to the uninitiated. Adding to the updated discussions of research design, hypothesis testing, regression analysis, and Bayes procedures, are new discussions of absolute and relative risk, as well as a lucid description of the number needed to treat (NNT). The multiple analysis issue is clearly defined, and a new description of the correct use and interpretation of combined endpoints in health care research is offered in an easily digestible format.The P-value Primer 2nd Edition demolishes other obstacles that have impeded a clear understanding of the application of statistics in medicine. The intertwined roles of epidemiology and biostatistics are depicted. In addition to a description of the non-technical history of statistics, a new discussion describes the active cultural forces that have historically argued against the use of probability and statistics, placing the current applications and controversies involving p-values in context. New illustrations of the difficulties physicians and health care providers face in research are offered, and the differences between research skills and statistical skills are distinguished. New discussion describing the process of scientific reasoning, p-values, and the law is included. All of this nonstandard content, so essential for a well rounded perspective on the modern use of statistics in medicine, makes this volume unique among introductory statistics books.New figures, conversation, and illustrations fortify each chapter. In addition, three new appendices have been added on the normal distribution, sample size computations, and new requirements for the use of statistics in the courtroom.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru