Handbook of matching and weighting adjustments for causal inference,
Автор: B. Sreenivasulu et al. Название: Causality Tests In Econometrics: Choice of Causal Variables ISBN: 3659504041 ISBN-13(EAN): 9783659504044 Издательство: LAP LAMBERT Academic Publishing Рейтинг: Цена: 49810.00 T Наличие на складе: Нет в наличии. Описание: In the Present Book Chapter-I is an introductory one.Chapter-II describes the concept and causal relations by econometric models. It presents the different representations such as autoregressive, Moving – average and univariate representation of causality. Chapter-III explore lucidly the various tests for causality, we come across in econometrics. In regression analysis, researchers are interested in testing for the exogenity of variables this testing is closely related to the causality test proposed by Granger, which is explained in detail in this chapter. Chapter-IV gives the conclusions about the present study.The various relevant research articles have been presented under the title BIBLIOGRAPHY.
Автор: Imbens Название: Causal Inference for Statistics, Social, and Biomedical Sciences ISBN: 0521885884 ISBN-13(EAN): 9780521885881 Издательство: Cambridge Academ Рейтинг: Цена: 54910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
Автор: Carroll, Raymond J. , Ruppert, David Название: Transformation and Weighting in Regression ISBN: 0367403374 ISBN-13(EAN): 9780367403379 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research.
While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.
Автор: Richard Valliant; Jill A. Dever; Frauke Kreuter Название: Practical Tools for Designing and Weighting Survey Samples ISBN: 3030066983 ISBN-13(EAN): 9783030066987 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The goal of this book is to put an array of tools at the fingertips of students, practitioners, and researchers by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This volume serves at least three audiences: (1) students of applied sampling techniques; 2) practicing survey statisticians applying concepts learned in theoretical or applied sampling courses; and (3) social scientists and other survey practitioners who design, select, and weight survey samples.The text thoroughly covers fundamental aspects of survey sampling, such as sample size calculation (with examples for both single- and multi-stage sample design) and weight computation, accompanied by software examples to facilitate implementation. Features include step-by-step instructions for calculating survey weights, extensive real-world examples and applications, and representative programming code in R, SAS, and other packages.Since the publication of the first edition in 2013, there have been important developments in making inferences from nonprobability samples, in address-based sampling (ABS), and in the application of machine learning techniques for survey estimation. New to this revised and expanded edition:• Details on new functions in the PracTools package• Additional machine learning methods to form weighting classes• New coverage of nonlinear optimization algorithms for sample allocation• Reflecting effects of multiple weighting steps (nonresponse and calibration) on standard errors• A new chapter on nonprobability sampling• Additional examples, exercises, and updated references throughoutRichard Valliant, PhD, is Research Professor Emeritus at the Institute for Social Research at the University of Michigan and at the Joint Program in Survey Methodology at the University of Maryland. He is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and has been an Associate Editor of the Journal of the American Statistical Association, Journal of Official Statistics, and Survey Methodology. Jill A. Dever, PhD, is Senior Research Statistician at RTI International in Washington, DC. She is a Fellow of the American Statistical Association, Associate Editor for Survey Methodology and the Journal of Official Statistics, and an Assistant Research Professor in the Joint Program in Survey Methodology at the University of Maryland. She has served on several panels for the National Academy of Sciences and as a task force member for the American Association of Public Opinion Research’s report on nonprobability sampling. Frauke Kreuter, PhD, is Professor and Director of the Joint Program in Survey Methodology at the University of Maryland, Professor of Statistics and Methodology at the University of Mannheim, and Head of the Statistical Methods Research Department at the Institute for Employment Research (IAB) in N?rnberg, Germany. She is a Fellow of the American Statistical Association and has been Associate Editor of the Journal of the Royal Statistical Society, Journal of Official Statistics, Sociological Methods and Research, Survey Research Methods, Public Opinion Quarterly, American Sociological Review, and the Stata Journal<
Автор: Stephen L. Morgan, Christopher Winship Название: Counterfactuals and Causal Inference: Methods and Principles for Social Research, 2 ed. ISBN: 1107065070 ISBN-13(EAN): 9781107065079 Издательство: Cambridge Academ Рейтинг: Цена: 90810.00 T 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.
Автор: Carroll, Raymond J. Название: Transformation and Weighting in Regression ISBN: 0412014211 ISBN-13(EAN): 9780412014215 Издательство: Taylor&Francis Рейтинг: Цена: 183750.00 T Наличие на складе: Нет в наличии.
Автор: Devin Caughey, Adam J. Berinskey, Sara Chatfield, Название: Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias ISBN: 1108794157 ISBN-13(EAN): 9781108794152 Издательство: Cambridge Academ Рейтинг: Цена: 19010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Nonresponse and other sources of bias are endemic features of public opinion surveys. We elaborate a general workflow of weighting-based survey inference, and describe in detail how this can be applied to the analysis of historical and contemporary opinion polls.
Автор: Valliant Название: Practical Tools for Designing and Weighting Survey Samples ISBN: 331993631X ISBN-13(EAN): 9783319936314 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The goal of this book is to put an array of tools at the fingertips of students, practitioners, and researchers by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed.
Название: Statistical Methods for Dynamic Treatment Regimes ISBN: 1461474272 ISBN-13(EAN): 9781461474272 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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.
Автор: Daniels, Michael J. Название: Bayesian nonparametrics for causal inference and missing data ISBN: 036734100X ISBN-13(EAN): 9780367341008 Издательство: Taylor&Francis Рейтинг: Цена: 100030.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Xiong, Momiao (university Of Texas School Of Public Health, Usa) Название: Artificial intelligence and causal inference ISBN: 0367859408 ISBN-13(EAN): 9780367859404 Издательство: Taylor&Francis Рейтинг: Цена: 107190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Artificial Intelligence and Causal Inference address the recent development of relationships between artificial intelligence (AI) and causal inference. Despite significant progress in AI, a great challenge in AI development we are still facing is to understand mechanism underlying intelligence, including reasoning, planning and imagination.
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