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Author: Vanessa Bergeron-Laperrière Publisher: ISBN: Category : Languages : en Pages :
Book Description
"In their paper "Toward a Curse of Dimensionality Appropriate (CODA) Asymptotic Theory for Semi-Parametric Models", Robins and Ritov (1997) introduced a missing data problem, with semiparametric model, for which it was said that the natural, sensible Bayesian approach failed, while the classical (frequentist) approach gave solutions with good asymptotic properties. We will explore their results after having studied the theory of missing data and semiparametric models. We will then show how a correct formulation of the problem using measure theory leads to natural Bayesian solutions with the same properties as the frequentist ones. We will finally give some simulation results to compare the different estimators introduced throughout." --
Author: Vanessa Bergeron-Laperrière Publisher: ISBN: Category : Languages : en Pages :
Book Description
"In their paper "Toward a Curse of Dimensionality Appropriate (CODA) Asymptotic Theory for Semi-Parametric Models", Robins and Ritov (1997) introduced a missing data problem, with semiparametric model, for which it was said that the natural, sensible Bayesian approach failed, while the classical (frequentist) approach gave solutions with good asymptotic properties. We will explore their results after having studied the theory of missing data and semiparametric models. We will then show how a correct formulation of the problem using measure theory leads to natural Bayesian solutions with the same properties as the frequentist ones. We will finally give some simulation results to compare the different estimators introduced throughout." --
Author: Anastasios Tsiatis Publisher: Springer Science & Business Media ISBN: 0387373454 Category : Mathematics Languages : en Pages : 392
Book Description
This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.
Author: Nicholas P. Jewell Publisher: Springer Science & Business Media ISBN: 1475712294 Category : Medical Languages : en Pages : 413
Book Description
In 1974, the Societal Institute of the Mathematical Sciences (SIMS) initiated a series of five-day Research Application Conferences (RAC's) at Alta, Utah, for the purpose of probing in depth societal fields in light of their receptivity to mathematical and statistical analysis. The first eleven conferences addressed ecosystems, epidemiology, energy, environmental health, time series and ecological processes, energy and health, energy conversion and fluid mechanics, environmental epidemiology: risk assessment, atomic bomb survival data: utilization and analysis, modem statistical methods in chronic disease epidemiology and scientific issues in quantitative cancer risk assess ment. These Proceedings are a result of the twelfth conference on Statistical Methodology for Study of the AIDS Epidemic which was held in 1991 at the Mathematical Sciences Research Institute, Berkeley, California. For five days, 45 speakers and observers contributed their expertise in the relevant biology and statistics. The presentations were timely and the discussion was both enlightening and at times spirited. Members of the Program Committee for the Conference were Klaus Dietz (University of Tiibingen, Germany), Vernon T. Farewell (University of Waterloo, Ontario), and Nicholas P. Jewell (University of California, Berke ley) (Chair). The Conference was supported by a grant to SIMS from the National Institute of Drug Abuse. D. L. Thomsen, Jr.
Author: M.Elizabeth Halloran Publisher: Springer Science & Business Media ISBN: 9780387989242 Category : Medical Languages : en Pages : 300
Book Description
This IMA Volume in Mathematics and its Applications STATISTICAL MODELS IN EPIDEMIOLOGY, THE ENVIRONMENT,AND CLINICAL TRIALS is a combined proceedings on "Design and Analysis of Clinical Trials" and "Statistics and Epidemiology: Environment and Health. " This volume is the third series based on the proceedings of a very successful 1997 IMA Summer Program on "Statistics in the Health Sciences. " I would like to thank the organizers: M. Elizabeth Halloran of Emory University (Biostatistics) and Donald A. Berry of Duke University (Insti tute of Statistics and Decision Sciences and Cancer Center Biostatistics) for their excellent work as organizers of the meeting and for editing the proceedings. I am grateful to Seymour Geisser of University of Minnesota (Statistics), Patricia Grambsch, University of Minnesota (Biostatistics); Joel Greenhouse, Carnegie Mellon University (Statistics); Nicholas Lange, Harvard Medical School (Brain Imaging Center, McLean Hospital); Barry Margolin, University of North Carolina-Chapel Hill (Biostatistics); Sandy Weisberg, University of Minnesota (Statistics); Scott Zeger, Johns Hop kins University (Biostatistics); and Marvin Zelen, Harvard School of Public Health (Biostatistics) for organizing the six weeks summer program. I also take this opportunity to thank the National Science Foundation (NSF) and the Army Research Office (ARO), whose financial support made the workshop possible. Willard Miller, Jr.
Author: Danyu Lin Publisher: Springer Science & Business Media ISBN: 1468463160 Category : Medical Languages : en Pages : 314
Book Description
The papers in this volume discuss important methodological advances in several important areas, including multivariate failure time data and interval censored data. The book will be an indispensable reference for researchers and practitioners in biostatistics, medical research, and the health sciences.
Author: M.Elizabeth Halloran Publisher: Springer Science & Business Media ISBN: 1461212847 Category : Medical Languages : en Pages : 287
Book Description
This IMA Volume in Mathematics and its Applications STATISTICAL MODELS IN EPIDEMIOLOGY, THE ENVIRONMENT,AND CLINICAL TRIALS is a combined proceedings on "Design and Analysis of Clinical Trials" and "Statistics and Epidemiology: Environment and Health. " This volume is the third series based on the proceedings of a very successful 1997 IMA Summer Program on "Statistics in the Health Sciences. " I would like to thank the organizers: M. Elizabeth Halloran of Emory University (Biostatistics) and Donald A. Berry of Duke University (Insti tute of Statistics and Decision Sciences and Cancer Center Biostatistics) for their excellent work as organizers of the meeting and for editing the proceedings. I am grateful to Seymour Geisser of University of Minnesota (Statistics), Patricia Grambsch, University of Minnesota (Biostatistics); Joel Greenhouse, Carnegie Mellon University (Statistics); Nicholas Lange, Harvard Medical School (Brain Imaging Center, McLean Hospital); Barry Margolin, University of North Carolina-Chapel Hill (Biostatistics); Sandy Weisberg, University of Minnesota (Statistics); Scott Zeger, Johns Hop kins University (Biostatistics); and Marvin Zelen, Harvard School of Public Health (Biostatistics) for organizing the six weeks summer program. I also take this opportunity to thank the National Science Foundation (NSF) and the Army Research Office (ARO), whose financial support made the workshop possible. Willard Miller, Jr.
Author: Michael J. Daniels Publisher: CRC Press ISBN: 1000927717 Category : Mathematics Languages : en Pages : 263
Book Description
Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest, such as missing at random assumption for missing data and unconfoundedness for causal inference in observational studies. Unlike parametric methods, the BNP approach can account for possible violations of assumptions and minimize concerns about model misspecification. The overall strategy is to first specify BNP models for observed data and then to specify additional uncheckable assumptions to identify estimands of interest. The book is divided into three parts. Part I develops the key concepts in causal inference and missing data and reviews relevant concepts in Bayesian inference. Part II introduces the fundamental BNP tools required to address causal inference and missing data problems. Part III shows how the BNP approach can be applied in a variety of case studies. The datasets in the case studies come from electronic health records data, survey data, cohort studies, and randomized clinical trials. Features • Thorough discussion of both BNP and its interplay with causal inference and missing data • How to use BNP and g-computation for causal inference and non-ignorable missingness • How to derive and calibrate sensitivity parameters to assess sensitivity to deviations from uncheckable causal and/or missingness assumptions • Detailed case studies illustrating the application of BNP methods to causal inference and missing data • R code and/or packages to implement BNP in causal inference and missing data problems The book is primarily aimed at researchers and graduate students from statistics and biostatistics. It will also serve as a useful practical reference for mathematically sophisticated epidemiologists and medical researchers.
Author: Mark J. van der Laan Publisher: Springer Science & Business Media ISBN: 0387217002 Category : Mathematics Languages : en Pages : 412
Book Description
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.
Author: Guido W. Imbens Publisher: Cambridge University Press ISBN: 0521885884 Category : Business & Economics Languages : en Pages : 647
Book Description
This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
Author: Vanessa Bergeron-Laperrière
Author: Vanessa Bergeron-Laperrière
Author: Anastasios Tsiatis
Author: Nicholas P. Jewell
Author: M.Elizabeth Halloran
Author: Danyu Lin
Author: M.Elizabeth Halloran
Author: Michael J. Daniels
Author: Mark J. van der Laan
Author: Guido W. Imbens
Author: