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Causal Inference for Statistics, Social, and Biomedical Sciences, Imbens



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Цена: 7918р.
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Автор: Imbens
Название:  Causal Inference for Statistics, Social, and Biomedical Sciences
Перевод названия: Имбенс: Причинно-следственная связь в статистике, социальных и биомедицинских науках
ISBN: 9780521885881
Издательство: Cambridge Academ
Классификация:
ISBN-10: 0521885884
Обложка/Формат: Hardback
Страницы: 644
Вес: 1.304 кг.
Дата издания: 06.04.2015
Серия: Economics/Business/Finance
Язык: English
Иллюстрации: 97 tables, unspecified; 18 line drawings, unspecified
Размер: 188 x 262 x 36
Читательская аудитория: Professional and scholarly
Ключевые слова: Economics of industrial organisation,Health economics,Epidemiology & medical statistics,Probability & statistics, MATHEMATICS / Probability & Statistics / General
Основная тема: Statistics and probability
Подзаголовок: An Introduction
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.


Counterfactuals and Causal Inference

Автор: Morgan
Название: Counterfactuals and Causal Inference
ISBN: 1107694167 ISBN-13(EAN): 9781107694163
Издательство: Cambridge Academ
Рейтинг:
Цена: 5542 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Cause-and-effect questions are the motivation for most research in the social, demographic, and health sciences. The counterfactual approach to causal analysis represents a unified framework for the prosecution of these questions. This second edition aims to convince more social scientists to take this approach when analyzing these core empirical questions.

Explanation in Causal Inference

Автор: VanderWeele Tyler
Название: Explanation in Causal Inference
ISBN: 0199325871 ISBN-13(EAN): 9780199325870
Издательство: Oxford Academ
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Цена: 18216 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The book provides an accessible but comprehensive overview of methods for mediation and interaction. There has been considerable and rapid methodological development on mediation and moderation/interaction analysis within the causal-inference literature over the last ten years. Much of this
material appears in a variety of specialized journals, and some of the papers are quite technical. There has also been considerable interest in these developments from empirical researchers in the social and biomedical sciences. However, much of the material is not currently in a format that is
accessible to them. The book closes these gaps by providing an accessible, comprehensive, book-length coverage of mediation.

The book begins with a comprehensive introduction to mediation analysis, including chapters on concepts for mediation, regression-based methods, sensitivity analysis, time-to-event outcomes, methods for multiple mediators, methods for time-varying mediation and longitudinal data, and relations
between mediation and other concepts involving intermediates such as surrogates, principal stratification, instrumental variables, and Mendelian randomization. The second part of the book concerns interaction or "moderation," including concepts for interaction, statistical interaction, confounding
and interaction, mechanistic interaction, bias analysis for interaction, interaction in genetic studies, and power and sample-size calculation for interaction. The final part of the book provides comprehensive discussion about the relationships between mediation and interaction and unites these
concepts within a single framework. This final part also provides an introduction to spillover effects or social interaction, concluding with a discussion of social-network analyses.

The book is written to be accessible to anyone with a basic knowledge of statistics. Comprehensive appendices provide more technical details for the interested reader. Applied empirical examples from a variety of fields are given throughout. Software implementation in SAS, Stata, SPSS, and R is
provided. The book should be accessible to students and researchers who have completed a first-year graduate sequence in quantitative methods in one of the social- or biomedical-sciences disciplines. The book will only presuppose familiarity with linear and logistic regression, and could potentially
be used as an advanced undergraduate book as well.

Methods for estimation and inference in modern econometrics

Автор: Anatolyev, Stanislav Gospodinov, Nikolay
Название: Methods for estimation and inference in modern econometrics
ISBN: 1439838240 ISBN-13(EAN): 9781439838242
Издательство: Taylor&Francis
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Цена: 14083 р.
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Описание:

Methods for Estimation and Inference in Modern Econometrics provides a comprehensive introduction to a wide range of emerging topics, such as generalized empirical likelihood estimation and alternative asymptotics under drifting parameterizations, which have not been discussed in detail outside of highly technical research papers. The book also addresses several problems often arising in the analysis of economic data, including weak identification, model misspecification, and possible nonstationarity. The book's appendix provides a review of some basic concepts and results from linear algebra, probability theory, and statistics that are used throughout the book.





Topics covered include:







  • Well-established nonparametric and parametric approaches to estimation and conventional (asymptotic and bootstrap) frameworks for statistical inference


  • Estimation of models based on moment restrictions implied by economic theory, including various method-of-moments estimators for unconditional and conditional moment restriction models, and asymptotic theory for correctly specified and misspecified models


  • Non-conventional asymptotic tools that lead to improved finite sample inference, such as higher-order asymptotic analysis that allows for more accurate approximations via various asymptotic expansions, and asymptotic approximations based on drifting parameter sequences






Offering a unified approach to studying econometric problems, Methods for Estimation and Inference in Modern Econometrics links most of the existing estimation and inference methods in a general framework to help readers synthesize all aspects of modern econometric theory. Various theoretical exercises and suggested solutions are included to facilitate understanding.

Statistical Causal Inferences and Their Applications in Public Health Research

Автор: He
Название: Statistical Causal Inferences and Their Applications in Public Health Research
ISBN: 3319412574 ISBN-13(EAN): 9783319412573
Издательство: Springer
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Цена: 15372 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in statistics, biostatistics, and computational biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.

Essential Statistical Inference

Автор: Boos
Название: Essential Statistical Inference
ISBN: 1461448174 ISBN-13(EAN): 9781461448174
Издательство: Springer
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Цена: 15372 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: A superb resource on statistical inference for researchers or students, this book has R code throughout, including in sample problems, and an appendix of derived notation and formulae. It covers core topics as well as modern aspects such as M-estimation.

A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935

Автор: Hald Anders
Название: A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935
ISBN: 0387464085 ISBN-13(EAN): 9780387464084
Издательство: Springer
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Цена: 16769 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of many ideas and developments. And unlike his other books, which were encyclopedic by nature, this book can be used for a course on the topic, the only prerequisites being a basic course in probability and statistics.The book is divided into five main sections:* Binomial statistical inference;* Statistical inference by inverse probability;* The central limit theorem and linear minimum variance estimation by Laplace and Gauss;* Error theory, skew distributions, correlation, sampling distributions;* The Fisherian Revolution, 1912-1935.Throughout each of the chapters, the author provides lively biographical sketches of many of the main characters, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. He also examines the roles played by DeMoivre, James Bernoulli, and Lagrange, and he provides an accessible exposition of the work of R.A. Fisher.This book will be of interest to statisticians, mathematicians, undergraduate and graduate students, and historians of science.


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