Bayesian Nonparametrics For Causal Inference And Missing Data
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Bayesian Nonparametrics For Causal Inference And Missing Data
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Author : Michael J. Daniels
language : en
Publisher: CRC Press
Release Date : 2023-08-23
Bayesian Nonparametrics For Causal Inference And Missing Data written by Michael J. Daniels and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-23 with Mathematics categories.
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.
Nonparametric Bayesian Inference In Biostatistics
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Author : Riten Mitra
language : en
Publisher: Springer
Release Date : 2015-07-25
Nonparametric Bayesian Inference In Biostatistics written by Riten Mitra and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-25 with Medical categories.
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters cover: clinical trials, spatial inference, proteomics, genomics, clustering, survival analysis and ROC curve.
Strength In Numbers The Rising Of Academic Statistics Departments In The U S
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Author : Alan Agresti
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-02
Strength In Numbers The Rising Of Academic Statistics Departments In The U S written by Alan Agresti and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-02 with Mathematics categories.
Statistical science as organized in formal academic departments is relatively new. With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years. This book consists of a set of memoirs, one for each department in the U.S. created by the mid-1960s. The memoirs describe key aspects of the department’s history -- its founding, its growth, key people in its development, success stories (such as major research accomplishments) and the occasional failure story, PhD graduates who have had a significant impact, its impact on statistical education, and a summary of where the department stands today and its vision for the future. Read here all about how departments such as at Berkeley, Chicago, Harvard, and Stanford started and how they got to where they are today. The book should also be of interests to scholars in the field of disciplinary history.
Bayesian Nonparametrics
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Author :
language : en
Publisher:
Release Date : 2010
Bayesian Nonparametrics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Bayesian statistical decision theory categories.
"Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount of data. Computational issues, though challenging, are no longer intractable. All that is needed is an entry point: this intelligent book is the perfect guide to what can seem a forbidding landscape. Tutorial chapters by Ghosal, Lijoi and Prünster, Teh and Jordan, and Dunson advance from theory, to basic models and hierarchical modeling, to applications and implementation, particularly in computer science and biostatistics. These are complemented by companion chapters by the editors and Griffin and Quintana, providing additional models, examining computational issues, identifying future growth areas, and giving links to related topics. This coherent text gives ready access both to underlying principles and to state-of-the-art practice. Specific examples are drawn from information retrieval, NLP, machine vision, computational biology, biostatistics, and bioinformatics"--Provided by publisher
Statistica Sinica
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Author :
language : en
Publisher:
Release Date : 2005
Statistica Sinica written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Mathematical statistics categories.
Causal Inference In Statistics Social And Biomedical Sciences
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Author : Guido W. Imbens
language : en
Publisher: Cambridge University Press
Release Date : 2015-04-06
Causal Inference In Statistics Social And Biomedical Sciences written by Guido W. Imbens and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-06 with Business & Economics categories.
This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
Modern Analysis Of Customer Surveys
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Author : Ron S. Kenett
language : en
Publisher: John Wiley & Sons
Release Date : 2012-01-30
Modern Analysis Of Customer Surveys written by Ron S. Kenett and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-30 with Business & Economics categories.
Modern Analysis of Customer Surveys: with applications using R Customer survey studies deal with customer, consumer and user satisfaction from a product or service. In practice, many of the customer surveys conducted by business and industry are analyzed in a very simple way, without using models or statistical methods. Typical reports include descriptive statistics and basic graphical displays. This book demonstrates how integrating such basic analysis with more advanced tools, provides insights into non-obvious patterns and important relationships between the survey variables. This knowledge can significantly affect the conclusions derived from a survey. Key features: Provides an integrated case studies-based approach to analysing customer survey data. Presents a general introduction to customer surveys, within an organization’s business cycle. Contains classical techniques with modern and non standard tools. Focuses on probabilistic techniques from the area of statistics/data analysis and covers all major recent developments. Accompanied by a supporting website containing datasets and R scripts. Customer survey specialists, quality managers and market researchers will benefit from this book as well as specialists in marketing, data mining and business intelligence fields. www.wiley.com/go/modern_analysis STATISTICS IN PRACTICE A series of practical books outlining the use of statistical techniques in a wide range of applications areas: HUMAN AND BIOLOGICAL SCIENCES EARTH AND ENVIRONMENTAL SCIENCES INDUSTRY, COMMERCE AND FINANCE
Real Versus Nominal Value Economics
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2024-03-29
Real Versus Nominal Value Economics written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Business & Economics categories.
What is Real versus Nominal Value Economics In economics, nominal value refers to value measured in terms of absolute money amounts, whereas real value is considered and measured against the actual goods or services for which it can be exchanged at a given time. Real value takes into account inflation and the value of an asset in relation to its purchasing power. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Real versus nominal value (economics) Chapter 2: Inflation Chapter 3: Interest Chapter 4: Price elasticity of demand Chapter 5: GDP deflator Chapter 6: Real gross domestic product Chapter 7: Quantity theory of money Chapter 8: Marshallian demand function Chapter 9: Price index Chapter 10: Velocity of money Chapter 11: Price level Chapter 12: Real interest rate Chapter 13: Continuously compounded nominal and real returns Chapter 14: Equation of exchange Chapter 15: Competitive equilibrium Chapter 16: International dollar Chapter 17: Regression analysis Chapter 18: Earnings growth Chapter 19: McCallum rule Chapter 20: Relative purchasing power parity Chapter 21: Nominal income target (II) Answering the public top questions about real versus nominal value economics. (III) Real world examples for the usage of real versus nominal value economics in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Real versus Nominal Value Economics.
Bayesian Nonparametric Data Analysis
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Author : Peter Müller
language : en
Publisher: Springer
Release Date : 2015-06-17
Bayesian Nonparametric Data Analysis written by Peter Müller and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-17 with Mathematics categories.
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.
Proceedings Of The Section On Bayesian Statistical Science
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Author : American Statistical Association. Section on Bayesian Statistical Science
language : en
Publisher:
Release Date : 1998
Proceedings Of The Section On Bayesian Statistical Science written by American Statistical Association. Section on Bayesian Statistical Science and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Bayesian statistical decision theory categories.