Causal Analysis with Event History Data Using Stata, Blossfeld, Hans-Peter
Старое издание
Автор: Blossfeld Название: Event History Analysis With Stata ISBN: 1138070793 ISBN-13(EAN): 9781138070790 Издательство: Taylor&Francis Цена: 148010 T Описание: This volume provides an introduction to event history models using Stata, a widely used and powerful statistical program that provides tools for data analysis.
Автор: A. Colin Cameron, Pravin K. Trivedi Название: Microeconometrics Using Stata, Second Edition, Volumes I and II ISBN: 1597183598 ISBN-13(EAN): 9781597183598 Издательство: Taylor&Francis Рейтинг: Цена: 153120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Microeconometrics Using Stata, Second Edition is an invaluable reference for researchers and students interested in applied microeconometric methods.
Автор: Barry C. Edwards, Philip H. Pollock III Название: A Stata® Companion to Political Analysis ISBN: 1071815040 ISBN-13(EAN): 9781071815045 Издательство: Sage Publications Рейтинг: Цена: 63360.00 T Наличие на складе: Поставка под заказ. Описание: The Fifth Edition of A Stata® Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards teaches your students statistics by analyzing research-quality data in Stata. It follows the structure of Essentials of Political Analysis with software instructions, explanations of tests, and many exercises for practice.
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: Hooshang Nayebi Название: Advanced Statistics for Testing Assumed Causal Relationships ISBN: 3030547531 ISBN-13(EAN): 9783030547530 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Blossfeld, Hans-Peter Название: Causal Analysis with Event History Data Using Stata ISBN: 1032657782 ISBN-13(EAN): 9781032657783 Издательство: Taylor&Francis Рейтинг: Цена: 55110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This third edition of our book provides an updated introduction to event history modeling along with many instructive Stata examples. Using the latest Stata software, each of these practical examples develops a research question, points to useful contextual background information, gives a brief account of the underlying statistical concepts, describes the organization of input data and the application of Stata statistical procedures, and assists the reader in interpreting the content of the results obtained. Emphasizing the strengths and limitations of continuous-time event history analysis in different fields of social science applications, this book demonstrates that event history models provide a useful approach to uncover causal relation- ships or to map a system of causal relationships. In particular, this book demonstrates how long-term processes can be studied, how different forms of duration dependencies can be estimated using nonparametric, parametric and semiparametric models, and how parallel and interdependent dynamic systems can be analyzed from a causal-analytical point of view using the method of episode splitting. The book also shows how changing contextual information at the micro, meso and macro levels can be easily integrated into a dynamic analysis of longitudinal data. Finally, the book addresses the problem of unobserved heterogeneity of time-constant and time-dependent omitted variables and makes suggestions for dealing with these sometimes difficult methodological problems.Causal Analysis with Event History Data Using Stata is an invaluable resource for both novice and experienced researchers from a variety of fields (e.g. sociology, economics, political science, education, psychology, demography, epidemiology, management research and organizational studies, as well as medicine and clinical applications) who need an introductory text- book on continuous-time event history analysis and who are looking for a practical handboo
Автор: Maziarz, Mariusz Название: The Philosophy of Causality in Economics ISBN: 0367363992 ISBN-13(EAN): 9780367363994 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Нет в наличии. Описание: What do economists mean when they conclude that A `causes` B? Does `cause` say that we can influence B by intervening on A, or is it only a label for the correlation of variables? This book analyses the meaning of causal claims made by economists and the philosophical presuppositions underlying the research methods used.
Автор: Carolyn R. Fawcett; S. Mehlberg; Paul Benacerraf; Название: Time, Causality, and the Quantum Theory ISBN: 9027707219 ISBN-13(EAN): 9789027707215 Издательство: Springer Рейтинг: Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: After relatively short academic appointments at the University of Toronto and at Princeton University, he taught at the University of Chicago until reaching the age of normal retirement.
Автор: Maziarz, Mariusz Название: The Philosophy of Causality in Economics ISBN: 0367494353 ISBN-13(EAN): 9780367494353 Издательство: Taylor&Francis Рейтинг: Цена: 51030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: What do economists mean when they conclude that A `causes` B? Does `cause` say that we can influence B by intervening on A, or is it only a label for the correlation of variables? This book analyses the meaning of causal claims made by economists and the philosophical presuppositions underlying the research methods used.
Автор: Stein, Nathanael (associate Professor Of Philosophy, Associate Professor Of Philosophy, Florida State University) Название: Causality and causal explanation in aristotle ISBN: 019766086X ISBN-13(EAN): 9780197660867 Издательство: Oxford Academ Рейтинг: Цена: 57030.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Federica Russo Название: Causality and Causal Modelling in the Social Sciences ISBN: 9048179963 ISBN-13(EAN): 9789048179961 Издательство: Springer Рейтинг: Цена: 139750.00 T 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.
Автор: Faries Douglas, Zhang Xiang, Kadziola Zbigniew Название: Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS ISBN: 1642957984 ISBN-13(EAN): 9781642957983 Издательство: Неизвестно Рейтинг: Цена: 104160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Discover best practices for real world data research with SAS code and examples
Real world health care data is common and growing in use with sources such as observational studies, patient registries, electronic medical record databases, insurance healthcare claims databases, as well as data from pragmatic trials. This data serves as the basis for the growing use of real world evidence in medical decision-making. However, the data itself is not evidence. Analytical methods must be used to turn real world data into valid and meaningful evidence. Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS brings together best practices for causal comparative effectiveness analyses based on real world data in a single location and provides SAS code and examples to make the analyses relatively easy and efficient.
The book focuses on analytic methods adjusted for time-independent confounding, which are useful when comparing the effect of different potential interventions on some outcome of interest when there is no randomization. These methods include:
propensity score matching, stratification methods, weighting methods, regression methods, and approaches that combine and average across these methods
methods for comparing two interventions as well as comparisons between three or more interventions
algorithms for personalized medicine
sensitivity analyses for unmeasured confounding
Автор: Faries Douglas, Zhang Xiang, Kadziola Zbigniew Название: Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS ISBN: 1642958026 ISBN-13(EAN): 9781642958027 Издательство: Неизвестно Рейтинг: Цена: 134810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Discover best practices for real world data research with SAS code and examples
Real world health care data is common and growing in use with sources such as observational studies, patient registries, electronic medical record databases, insurance healthcare claims databases, as well as data from pragmatic trials. This data serves as the basis for the growing use of real world evidence in medical decision-making. However, the data itself is not evidence. Analytical methods must be used to turn real world data into valid and meaningful evidence. Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS brings together best practices for causal comparative effectiveness analyses based on real world data in a single location and provides SAS code and examples to make the analyses relatively easy and efficient.
The book focuses on analytic methods adjusted for time-independent confounding, which are useful when comparing the effect of different potential interventions on some outcome of interest when there is no randomization. These methods include:
propensity score matching, stratification methods, weighting methods, regression methods, and approaches that combine and average across these methods
methods for comparing two interventions as well as comparisons between three or more interventions
algorithms for personalized medicine
sensitivity analyses for unmeasured confounding
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