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Handbook Of Matching And Weighting Adjustments For Causal Inference


Handbook Of Matching And Weighting Adjustments For Causal Inference
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Handbook Of Matching And Weighting Adjustments For Causal Inference


Handbook Of Matching And Weighting Adjustments For Causal Inference
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Author : José R. Zubizarreta
language : en
Publisher: CRC Press
Release Date : 2023-04-11

Handbook Of Matching And Weighting Adjustments For Causal Inference written by José R. Zubizarreta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Mathematics categories.


An observational study infers the effects caused by a treatment, policy, program, intervention, or exposure in a context in which randomized experimentation is unethical or impractical. One task in an observational study is to adjust for visible pretreatment differences between the treated and control groups. Multivariate matching and weighting are two modern forms of adjustment. This handbook provides a comprehensive survey of the most recent methods of adjustment by matching, weighting, machine learning and their combinations. Three additional chapters introduce the steps from association to causation that follow after adjustments are complete. When used alone, matching and weighting do not use outcome information, so they are part of the design of an observational study. When used in conjunction with models for the outcome, matching and weighting may enhance the robustness of model-based adjustments. The book is for researchers in medicine, economics, public health, psychology, epidemiology, public program evaluation, and statistics who examine evidence of the effects on human beings of treatments, policies or exposures.



Handbook Of Bayesian Fiducial And Frequentist Inference


Handbook Of Bayesian Fiducial And Frequentist Inference
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Author : James Berger
language : en
Publisher: CRC Press
Release Date : 2024-02-26

Handbook Of Bayesian Fiducial And Frequentist Inference written by James Berger and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-26 with Mathematics categories.


The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference. Despite the tremendous progress that has been made, statistical science is still a young discipline and continues to have several different and competing paths in its approaches and its foundations. While the emergence of competing approaches is a natural progression of any scientific discipline, differences in the foundations of statistical inference can sometimes lead to different interpretations and conclusions from the same dataset. The increased interest in the foundations of statistical inference has led to many publications, and recent vibrant research activities in statistics, applied mathematics, philosophy and other fields of science reflect the importance of this development. The BFF approaches not only bridge foundations and scientific learning, but also facilitate objective and replicable scientific research, and provide scalable computing methodologies for the analysis of big data. Most of the published work typically focusses on a single topic or theme, and the body of work is scattered in different journals. This handbook provides a comprehensive introduction and broad overview of the key developments in the BFF schools of inference. It is intended for researchers and students who wish for an overview of foundations of inference from the BFF perspective and provides a general reference for BFF inference. Key Features: Provides a comprehensive introduction to the key developments in the BFF schools of inference Gives an overview of modern inferential methods, allowing scientists in other fields to expand their knowledge Is accessible for readers with different perspectives and backgrounds



Propensity Score Analysis


Propensity Score Analysis
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Author : Wei Pan
language : en
Publisher: Guilford Publications
Release Date : 2015-04-07

Propensity Score Analysis written by Wei Pan and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-07 with Psychology categories.


This book is designed to help researchers better design and analyze observational data from quasi-experimental studies and improve the validity of research on causal claims. It provides clear guidance on the use of different propensity score analysis (PSA) methods, from the fundamentals to complex, cutting-edge techniques. Experts in the field introduce underlying concepts and current issues and review relevant software programs for PSA. The book addresses the steps in propensity score estimation, including the use of generalized boosted models, how to identify which matching methods work best with specific types of data, and the evaluation of balance results on key background covariates after matching. Also covered are applications of PSA with complex data, working with missing data, controlling for unobserved confounding, and the extension of PSA to prognostic score analysis for causal inference. User-friendly features include statistical program codes and application examples. Data and software code for the examples are available at the companion website (www.guilford.com/pan-materials).



Handbook Of Design And Analysis Of Experiments


Handbook Of Design And Analysis Of Experiments
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Author : Angela Dean
language : en
Publisher: CRC Press
Release Date : 2015-06-26

Handbook Of Design And Analysis Of Experiments written by Angela Dean and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-26 with Mathematics categories.


This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.



Causal Inference In Statistics Social And Biomedical Sciences


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.



Handbook Of Mixed Membership Models And Their Applications


Handbook Of Mixed Membership Models And Their Applications
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Author : Edoardo M. Airoldi
language : en
Publisher: CRC Press
Release Date : 2014-11-06

Handbook Of Mixed Membership Models And Their Applications written by Edoardo M. Airoldi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-06 with Computers categories.


Incorporating more than 20 years of the editors' and contributors' statistical work in mixed membership modeling, this handbook shows how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, readers will discover how to characterize complex multivariate data in a range of areas.



The Wiley Handbook Of Psychometric Testing


The Wiley Handbook Of Psychometric Testing
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Author : Paul Irwing
language : en
Publisher: John Wiley & Sons
Release Date : 2018-02-12

The Wiley Handbook Of Psychometric Testing written by Paul Irwing 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 2018-02-12 with Education categories.


A must-have resource for researchers, practitioners, and advanced students interested or involved in psychometric testing Over the past hundred years, psychometric testing has proved to be a valuable tool for measuring personality, mental ability, attitudes, and much more. The word ‘psychometrics’ can be translated as ‘mental measurement’; however, the implication that psychometrics as a field is confined to psychology is highly misleading. Scientists and practitioners from virtually every conceivable discipline now use and analyze data collected from questionnaires, scales, and tests developed from psychometric principles, and the field is vibrant with new and useful methods and approaches. This handbook brings together contributions from leading psychometricians in a diverse array of fields around the globe. Each provides accessible and practical information about their specialist area in a three-step format covering historical and standard approaches, innovative issues and techniques, and practical guidance on how to apply the methods discussed. Throughout, real-world examples help to illustrate and clarify key aspects of the topics covered. The aim is to fill a gap for information about psychometric testing that is neither too basic nor too technical and specialized, and will enable researchers, practitioners, and graduate students to expand their knowledge and skills in the area. Provides comprehensive coverage of the field of psychometric testing, from designing a test through writing items to constructing and evaluating scales Takes a practical approach, addressing real issues faced by practitioners and researchers Provides basic and accessible mathematical and statistical foundations of all psychometric techniques discussed Provides example software code to help readers implement the analyses discussed



Multivariate Analysis Of Variance And Repeated Measures


Multivariate Analysis Of Variance And Repeated Measures
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Author : David J. Hand
language : en
Publisher: CRC Press
Release Date : 1987-05-01

Multivariate Analysis Of Variance And Repeated Measures written by David J. Hand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987-05-01 with Mathematics categories.


This book describes a practical aproach to univariate and multivariate analysis of variance. It starts with a general non-mathematical account of the fundamental theories and this is followed by a discussion of a series of examples using real data sets from the authors' own work in clinical trials, psychology and industry. Included are discussions of factorial and nested designs, structures on the multiple dependent variables measured on each subject, repeated measures analyses, covariates, choice of text statistic and simultaneous test procedures.



Handbook Of Bayesian Variable Selection


Handbook Of Bayesian Variable Selection
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Author : Mahlet G. Tadesse
language : en
Publisher: CRC Press
Release Date : 2021-12-24

Handbook Of Bayesian Variable Selection written by Mahlet G. Tadesse and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-24 with Mathematics categories.


Bayesian variable selection has experienced substantial developments over the past 30 years with the proliferation of large data sets. Identifying relevant variables to include in a model allows simpler interpretation, avoids overfitting and multicollinearity, and can provide insights into the mechanisms underlying an observed phenomenon. Variable selection is especially important when the number of potential predictors is substantially larger than the sample size and sparsity can reasonably be assumed. The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects of Bayesian methods for variable selection. The topics covered include spike-and-slab priors, continuous shrinkage priors, Bayes factors, Bayesian model averaging, partitioning methods, as well as variable selection in decision trees and edge selection in graphical models. The handbook targets graduate students and established researchers who seek to understand the latest developments in the field. It also provides a valuable reference for all interested in applying existing methods and/or pursuing methodological extensions. Features: Provides a comprehensive review of methods and applications of Bayesian variable selection. Divided into four parts: Spike-and-Slab Priors; Continuous Shrinkage Priors; Extensions to various Modeling; Other Approaches to Bayesian Variable Selection. Covers theoretical and methodological aspects, as well as worked out examples with R code provided in the online supplement. Includes contributions by experts in the field. Supported by a website with code, data, and other supplementary material



Handbook Of Approximate Bayesian Computation


Handbook Of Approximate Bayesian Computation
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Author : Scott A. Sisson
language : en
Publisher: CRC Press
Release Date : 2018-09-03

Handbook Of Approximate Bayesian Computation written by Scott A. Sisson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Mathematics categories.


As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of ABC methods. These simple, but powerful statistical techniques, take Bayesian statistics beyond the need to specify overly simplified models, to the setting where the model is defined only as a process that generates data. This process can be arbitrarily complex, to the point where standard Bayesian techniques based on working with tractable likelihood functions would not be viable. ABC methods finesse the problem of model complexity within the Bayesian framework by exploiting modern computational power, thereby permitting approximate Bayesian analyses of models that would otherwise be impossible to implement. The Handbook of ABC provides illuminating insight into the world of Bayesian modelling for intractable models for both experts and newcomers alike. It is an essential reference book for anyone interested in learning about and implementing ABC techniques to analyse complex models in the modern world.