Îïèñàíèå: 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.

Àâòîð: Bretz Íàçâàíèå: Multiple Comparisons Using R ISBN: 1584885742 ISBN-13(EAN): 9781584885740 Èçäàòåëüñòâî: Taylor&Francis Ðåéòèíã: Öåíà: 9816 ð. Íàëè÷èå íà ñêëàäå: Åñòü ó ïîñòàâùèêà Ïîñòàâêà ïîä çàêàç.

Îïèñàíèå: Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. Adopting a unifying theme based on maximum statistics, this self-contained introduction describes the common underlying theory of multiple comparison procedures through numerous examples. It covers a range of multiple comparison procedures, from the Bonferroni method and Simes’ test to resampling and adaptive design methods. The book also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org

The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe.

Îïèñàíèå: Discusses the application of statistical techniques to various aspects of modern medical research. This book illustrates how these methods prove to be an indispensable part of proper data collection and analysis. It discusses general concepts and the biomedical problem under focus. It details the associated methods, algorithms, and applications.

Îïèñàíèå: Conventional statistical methods have a very serious flaw. They routinely miss differences among groups or associations among variables that are detected by more modern techniques - even under very small departures from normality. Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable. Improved methods have been derived, but they are far from obvious or intuitive based on the training most researchers receive. Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods. Without assuming any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand. The emphasis is on verbal and graphical descriptions of concepts. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included to illustrate the practical problems with conventional procedures and how more modern methods can make a substantial difference in the conclusions reached in many areas of statistical research.Rand Wilcox is a professor of psychology at the University of Southern California. He is a fellow of the Royal Statistical Society and the American Psychological Society. Dr. Wilcox currently serves as an associate editor of Computational Statistics & Data Analysis and Psychometrika. He has published over 165 articles in a wide range of statistical journals and he is the author of three other books on statistics.|Â¿The volume is a jewel of direct explanations and information necessary for a good understanding of analysis of data, aimed at ordinary researchers who must try to present reasonable interpretable accounts of their data or judge when to abandon a particular strategy..."|- Perceptual and Motor Skills, 2002

Îïèñàíèå: Professionals in all areas ?“ business; government; the physical, life, and social sciences; engineering; medicine, etc. ?“ benefit from using statistical experimental design to better understand their worlds and then use that understanding to improve t

Îïèñàíèå: This book covers the basic statistical and analytical techniques of computer intrusion detection. It is aimed at both statisticians looking to become involved in the data analysis aspects of computer security and computer scientists looking to expand their toolbox of techniques for detecting intruders.The book is self-contained, assumng no expertise in either computer security or statistics. It begins with a description of the basics of TCP/IP, followed by chapters dealing with network traffic analysis, network monitoring for intrusion detection, host based intrusion detection, and computer viruses and other malicious code. Each section develops the necessary tools as needed. There is an extensive discussion of visualization as it relates to network data and intrusion detection. The book also contains a large bibliography covering the statistical, machine learning, and pattern recognition literature related to network monitoring and intrusion detection.

Îïèñàíèå: With increasing rates of pollution to both land and aquatic environments, regulations for the quality of waters are necessarily becoming more stringent. This book offers a practical guide to the statistical methods used for assessing health effects and monitoring and modelling water quality. It discuses both traditional and novel sampling designs.

Àâòîð: Laird Íàçâàíèå: The fundamentals of modern statistical genetics ISBN: 1441973370 ISBN-13(EAN): 9781441973375 Èçäàòåëüñòâî: Springer Ðåéòèíã: Öåíà: 8881 ð. Íàëè÷èå íà ñêëàäå: Åñòü ó ïîñòàâùèêà Ïîñòàâêà ïîä çàêàç.

Îïèñàíèå: This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.

Àâòîð: Coladarci Íàçâàíèå: Fundamentals of Statistical Reasoning in Education ISBN: 0470574798 ISBN-13(EAN): 9780470574799 Èçäàòåëüñòâî: Wiley Ðåéòèíã: Öåíà: 56999 ð. Íàëè÷èå íà ñêëàäå: Íåò â íàëè÷èè.