Active Statistics: Stories, Games, Problems, and Hands-on Demonstrations for Applied Regression and Causal Inference, Aki Vehtari, Andrew Gelman
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: 7472.00 р. 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.
Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
Название: Sage handbook of regression analysis and causal inference ISBN: 1446252442 ISBN-13(EAN): 9781446252444 Издательство: Sage Publications Рейтинг: Цена: 21384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Bibhas Chakraborty; Erica E.M. Moodie Название: Statistical Methods for Dynamic Treatment Regimes ISBN: 1489990305 ISBN-13(EAN): 9781489990303 Издательство: Springer Рейтинг: Цена: 6986.00 р. 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: Ding, Peng Название: A First Course in Causal Inference ISBN: 1032758627 ISBN-13(EAN): 9781032758626 Издательство: Taylor&Francis Рейтинг: Цена: 9951.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Morgan Название: Counterfactuals and Causal Inference ISBN: 1107694167 ISBN-13(EAN): 9781107694163 Издательство: Cambridge Academ Рейтинг: Цена: 5702.00 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.
Автор: Mark J. van der Laan; Sherri Rose Название: Targeted Learning in Data Science ISBN: 3319653032 ISBN-13(EAN): 9783319653037 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data.
Автор: Fang, Yixin Название: Causal Inference in Pharmaceutical Statistics ISBN: 1032560142 ISBN-13(EAN): 9781032560144 Издательство: Taylor&Francis Рейтинг: Цена: 15004.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Humphreys, Macartan (wissenschaftszentrum Berlin Fur Sozialforschung) Jacobs, Alan M. (university Of British Columbia, Vancouver) Название: Integrated inferences ISBN: 1316620662 ISBN-13(EAN): 9781316620663 Издательство: Cambridge Academ Рейтинг: Цена: 4750.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: There is a growing consensus in the social sciences on the virtues of research strategies that combine quantitative with qualitative tools of inference. Integrated Inferences develops a framework for using causal models and Bayesian updating for qualitative and mixed-methods research. By making, updating, and querying causal models, researchers are able to integrate information from different data sources while connecting theory and empirics in a far more systematic and transparent manner than standard qualitative and quantitative approaches allow. This book provides an introduction to fundamental principles of causal inference and Bayesian updating and shows how these tools can be used to implement and justify inferences using within-case (process tracing) evidence, correlational patterns across many cases, or a mix of the two. The authors also demonstrate how causal models can guide research design, informing choices about which cases, observations, and mixes of methods will be most useful for addressing any given question.
Автор: Federica Russo Название: Causality and Causal Modelling in the Social Sciences ISBN: 9048179963 ISBN-13(EAN): 9789048179961 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This investigation into causal modelling presents the rationale of causality; i.e. what guides reasoning in causal modeling. In contrast to the dominant paradigm, it argues that causal models are governed by a variation, rather than regularity or invariance.
Описание: It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable.
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.
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