observational studies springer series in statistics

Download Book Observational Studies Springer Series In Statistics in PDF format. You can Read Online Observational Studies Springer Series In Statistics here in PDF, EPUB, Mobi or Docx formats.

Design Of Observational Studies

Author : Paul R. Rosenbaum
ISBN : 9781441912138
Genre : Mathematics
File Size : 21. 32 MB
Format : PDF, Mobi
Download : 761
Read : 1002

Download Now


An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. Design of Observational Studies is divided into four parts. Chapters 2, 3, and 5 of Part I cover concisely, in about one hundred pages, many of the ideas discussed in Rosenbaum’s Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates. Part II includes a chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher’s striking advice for observational studies, "make your theories elaborate." The second edition of his book, Observational Studies, was published by Springer in 2002.

Observational Studies

Author : Paul R. Rosenbaum
ISBN : 9781475736922
Genre : Mathematics
File Size : 88. 21 MB
Format : PDF, ePub, Docs
Download : 691
Read : 1049

Download Now


A sound statistical account of the principles and methods for the design and analysis of observational studies. Readers are assumed to have a working knowledge of basic probability and statistics, but otherwise the account is reasonably self- contained. Throughout there are extended discussions of actual observational studies to illustrate the ideas discussed, drawn from topics as diverse as smoking and lung cancer, lead in children, nuclear weapons testing, and placement programs for students. As a result, many researchers will find this an invaluable companion in their work.

Targeted Learning

Author : Mark J. van der Laan
ISBN : 1441997822
Genre : Mathematics
File Size : 24. 90 MB
Format : PDF
Download : 380
Read : 168

Download Now


The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands of measurements for a single subject. The field is ready to move towards clear objective benchmarks under which tools can be evaluated. Targeted learning allows (1) the full generalization and utilization of cross-validation as an estimator selection tool so that the subjective choices made by humans are now made by the machine, and (2) targeting the fitting of the probability distribution of the data toward the target parameter representing the scientific question of interest. This book is aimed at both statisticians and applied researchers interested in causal inference and general effect estimation for observational and experimental data. Part I is an accessible introduction to super learning and the targeted maximum likelihood estimator, including related concepts necessary to understand and apply these methods. Parts II-IX handle complex data structures and topics applied researchers will immediately recognize from their own research, including time-to-event outcomes, direct and indirect effects, positivity violations, case-control studies, censored data, longitudinal data, and genomic studies.

Unified Methods For Censored Longitudinal Data And Causality

Author : Mark J. van der Laan
ISBN : 9780387217000
Genre : Mathematics
File Size : 77. 13 MB
Format : PDF
Download : 931
Read : 925

Download Now


A fundamental statistical framework for the analysis of complex longitudinal data is provided in this book. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures. The techniques go beyond standard statistical approaches and can be used to teach masters and Ph.D. students. The text is ideally suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.

Permutation Tests

Author : Phillip Good
ISBN : 9781475732351
Genre : Mathematics
File Size : 55. 66 MB
Format : PDF, ePub, Mobi
Download : 365
Read : 1305

Download Now


A step-by-step manual on the application of permutation tests in biology, business, medicine, science, and engineering. Its intuitive and informal style make it ideal for students and researchers, whether experienced or coming to these resampling methods for the first time. The real-world problems of missing and censored data, multiple comparisons, nonresponders, after-the-fact covariates, and outliers are all dealt with at length. This new edition has more than 100 additional pages, and includes streamlined statistics for the k-sample comparison and analysis of variance plus expanded sections on computational techniques, multiple comparisons, multiple regression, comparing variances, and testing interactions in balanced designs. The comprehensive author and subject indexes, plus an expert-system guide to methods, provide for further ease of use, while the exercises at the end of every chapter have been supplemented with drills and a number of graduate-level thesis problems.

Planning And Analysis Of Observational Studies

Author : William Gemmell Cochran
ISBN : UCAL:B4406676
Genre : Science
File Size : 81. 6 MB
Format : PDF, Mobi
Download : 794
Read : 1173

Download Now


Variation, control, and bias; Statistical introduction; Preliminary aspects of planning; Further aspects of planning; Matching; Adjustments in analysis; Simple study structures.

Matched Sampling For Causal Effects

Author : Donald B. Rubin
ISBN : 9781139458504
Genre : Mathematics
File Size : 84. 37 MB
Format : PDF
Download : 765
Read : 1319

Download Now


Matched sampling is often used to help assess the causal effect of some exposure or intervention, typically when randomized experiments are not available or cannot be conducted. This book presents a selection of Donald B. Rubin's research articles on matched sampling, from the early 1970s, when the author was one of the major researchers involved in establishing the field, to recent contributions to this now extremely active area. The articles include fundamental theoretical studies that have become classics, important extensions, and real applications that range from breast cancer treatments to tobacco litigation to studies of criminal tendencies. They are organized into seven parts, each with an introduction by the author that provides historical and personal context and discusses the relevance of the work today. A concluding essay offers advice to investigators designing observational studies. The book provides an accessible introduction to the study of matched sampling and will be an indispensable reference for students and researchers.

Statistical Methods For Dynamic Treatment Regimes

Author : Bibhas Chakraborty
ISBN : 9781461474289
Genre : Medical
File Size : 60. 24 MB
Format : PDF
Download : 523
Read : 1262

Download Now


Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine. This volume demonstrates these methods with their conceptual underpinnings and illustration through analysis of real and simulated data. These methods are immediately applicable to the practice of personalized medicine, which is a medical paradigm that emphasizes the systematic use of individual patient information to optimize patient health care. This is the first single source to provide an overview of methodology and results gathered from journals, proceedings, and technical reports with the goal of orienting researchers to the field. The first chapter establishes context for the statistical reader in the landscape of personalized medicine. Readers need only have familiarity with elementary calculus, linear algebra, and basic large-sample theory to use this text. Throughout the text, authors direct readers to available code or packages in different statistical languages to facilitate implementation. In cases where code does not already exist, the authors provide analytic approaches in sufficient detail that any researcher with knowledge of statistical programming could implement the methods from scratch. This will be an important volume for a wide range of researchers, including statisticians, epidemiologists, medical researchers, and machine learning researchers interested in medical applications. Advanced graduate students in statistics and biostatistics will also find material in Statistical Methods for Dynamic Treatment Regimes to be a critical part of their studies.

A Concise Guide To Observational Studies In Healthcare

Author : Allan Hackshaw
ISBN : 9780470658673
Genre : Medical
File Size : 66. 34 MB
Format : PDF, Kindle
Download : 558
Read : 805

Download Now


A Concise Guide to Observational Studies in Healthcare provides busy healthcare professionals with an easy-to-read introduction and overview to conducting, analysing and assessing observational studies. It is a suitable introduction for anyone without prior knowledge of study design, analysis or conduct as the important concepts are presented throughout the text. It provides an overview to the features of design, analyses and conduct of observational studies, without using mathematical formulae, or complex statistics or terminology and is a useful guide for researchers conducting their own studies, those who participate in studies co-ordinated by others, or who read or review a published report of an observational study. Examples are based on clinical features of people, biomarkers, lifestyle habits and environmental exposures, and evaluating quality of care. A Concise Guide to Observational Studies in Healthcare is a companion text to the popular A Concise Guide to Clinical Trials and is relevant for all healthcare professionals, clinical and health researchers, and medical students.

The Elements Of Statistical Learning

Author : Trevor Hastie
ISBN : 9780387216065
Genre : Mathematics
File Size : 76. 87 MB
Format : PDF, Kindle
Download : 983
Read : 240

Download Now


During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Top Download:

Best Books