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Journal of the Royal Statistical Society

Journal of the Royal Statistical Society PDF Author: Royal Statistical Society (Great Britain)
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 576

Book Description


Journal of the Royal Statistical Society

Journal of the Royal Statistical Society PDF Author: Royal Statistical Society (Great Britain)
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 576

Book Description


Journal of the Royal Statistical Society

Journal of the Royal Statistical Society PDF Author:
Publisher:
ISBN:
Category : Great Britain
Languages : en
Pages : 1000

Book Description


Supplement to the Journal of the Royal Statistical Society

Supplement to the Journal of the Royal Statistical Society PDF Author: Royal Statistical Society (Great Britain)
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 1648

Book Description


Replication and Evidence Factors in Observational Studies

Replication and Evidence Factors in Observational Studies PDF Author: Paul Rosenbaum
Publisher: CRC Press
ISBN: 100037002X
Category : Mathematics
Languages : en
Pages : 273

Book Description
Outside of randomized experiments, association does not imply causation, and yet there is nothing defective about our knowledge that smoking causes lung cancer, a conclusion reached in the absence of randomized experimentation with humans. How is that possible? If observed associations do not identify causal effects in observational studies, how can a sequence of such associations become decisive? Two or more associations may each be susceptible to unmeasured biases, yet not susceptible to the same biases. An observational study has two evidence factors if it provides two comparisons susceptible to different biases that may be combined as if from independent studies of different data by different investigators, despite using the same data twice. If the two factors concur, then they may exhibit greater insensitivity to unmeasured biases than either factor exhibits on its own. Replication and Evidence Factors in Observational Studies includes four parts: A concise introduction to causal inference, making the book self-contained Practical examples of evidence factors from the health and social sciences with analyses in R The theory of evidence factors Study design with evidence factors A companion R package evident is available from CRAN.

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives PDF Author: Andrew Gelman
Publisher: John Wiley & Sons
ISBN: 9780470090435
Category : Mathematics
Languages : en
Pages : 448

Book Description
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of the book include: Comprehensive coverage of an imporant area for both research and applications. Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques. Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference. Includes a number of applications from the social and health sciences. Edited and authored by highly respected researchers in the area.

Journal of the Royal Statistical Society

Journal of the Royal Statistical Society PDF Author: Royal Statistical Society (Great Britain)
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 980

Book Description
Published papers whose appeal lies in their subject-matter rather than their technical statistical contents. Medical, social, educational, legal,demographic and governmental issues are of particular concern.

Measuring Abundance

Measuring Abundance PDF Author: Graham Upton
Publisher: Pelagic Publishing Ltd
ISBN: 1784272337
Category : Science
Languages : en
Pages : 278

Book Description
Measuring the abundance of individuals and the diversity of species are core components of most ecological research projects and conservation monitoring. This book brings together in one place, for the first time, the methods used to estimate the abundance of individuals in nature. The statistical basis of each method is detailed along with practical considerations for survey design and data collection. Methods are illustrated using data ranging from Alaskan shrubs to Yellowstone grizzly bears, not forgetting Costa Rican ants and Prince Edward Island lobsters. Where necessary, example code for use with the open source software R is supplied. When appropriate, reference is made to other widely used programs. After opening with a brief synopsis of relevant statistical methods, the first section deals with the abundance of stationary items such as trees, shrubs, coral, etc. Following a discussion of the use of quadrats and transects in the contexts of forestry sampling and the assessment of plant cover, there are chapters addressing line-intercept sampling, the use of nearest-neighbour distances, and variable sized plots. The second section deals with individuals that move, such as birds, mammals, reptiles, fish, etc. Approaches discussed include double-observer sampling, removal sampling, capture-recapture methods and distance sampling. The final section deals with the measurement of species richness; species diversity; species-abundance distributions; and other aspects of diversity such as evenness, similarity, turnover and rarity. This is an essential reference for anyone involved in advanced undergraduate or postgraduate ecological research and teaching, or those planning and carrying out data analysis as part of conservation survey and monitoring programmes.

Analytic Methods in Sports

Analytic Methods in Sports PDF Author: Thomas A. Severini
Publisher: CRC Press
ISBN: 1000050947
Category : Mathematics
Languages : en
Pages : 362

Book Description
One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter. Features Covers numerous statistical procedures for analyzing data based on sports results Presents fundamental methods for describing and summarizing data Describes aspects of probability theory and basic statistical concepts that are necessary to understand and deal with the randomness inherent in sports data Explains the statistical reasoning underlying the methods Illustrates the methods using real data drawn from a wide variety of sports Offers many of the datasets on the author’s website, enabling you to replicate the analyses or conduct related analyses New to the Second Edition R code included for all calculations A new chapter discussing several more advanced methods, such as binary response models, random effects, multilevel models, spline methods, and principal components analysis, and more Exercises added to the end of each chapter, to enable use for courses and self-study

Breakthroughs in Statistics

Breakthroughs in Statistics PDF Author: Samuel Kotz
Publisher: Springer Science & Business Media
ISBN: 1461206677
Category : Mathematics
Languages : en
Pages : 576

Book Description
Volume III includes more selections of articles that have initiated fundamental changes in statistical methodology. It contains articles published before 1980 that were overlooked in the previous two volumes plus articles from the 1980's - all of them chosen after consulting many of today's leading statisticians.

Statistical Issues in Drug Development

Statistical Issues in Drug Development PDF Author: Stephen S. Senn
Publisher: John Wiley & Sons
ISBN: 9780470723579
Category : Medical
Languages : en
Pages : 523

Book Description
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.