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: 22202.00 р. Наличие на складе: Есть у поставщикаПоставка под заказ. 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: 22968.00 р. 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: 9504.00 р. 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: 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.
Автор: Hooshang Nayebi Название: Advanced Statistics for Testing Assumed Causal Relationships ISBN: 3030547531 ISBN-13(EAN): 9783030547530 Издательство: Springer Рейтинг: Цена: 11179.00 р. 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: Xiong, Momiao (university Of Texas School Of Public Health, Usa) Название: Big data in omics and imaging ISBN: 1032095237 ISBN-13(EAN): 9781032095233 Издательство: Taylor&Francis Рейтинг: Цена: 6889.00 р. Наличие на складе: Поставка под заказ.
Описание: Emerging genomic, epigenomic, sensing and image technologies will produce massive, dimensional genomic, epigenomic, physiological, image and clinical data. The book is designed to introduce the currently developed statistical methods and software for big genomic and epigenomic data analysis.
Автор: Thomas Cleff Название: Applied Statistics and Multivariate Data Analysis ISBN: 3030177661 ISBN-13(EAN): 9783030177669 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Поставка под заказ.
Описание: This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis.
In the past fifty years statisticians and methodologists in the social sciences have developed and refined a family of closely related statistical methods for the study of social phenomena. While the value of such methods of analysis is universally acknowledged, their use has never been wholly uncontroversial. In 1993 prominent scholars from a variety of disciplines (social sciences, statistics, philosophy of science) gathered at the University of Notre Dame to debate whether causal modeling techniques old or new can really justify the drawing of causal conclusions on the basis of correlational statistical data. The resulting volume from that groundbreaking conference is Causality in Crisis? a comprehensive and sophisticated introduction to perhaps the most important set of issues confronting social scientific researchers in the 1990s and beyond.
In the essays presented here contributors critically reassess the widely accepted view that statistical methods of analysis can and do yield causal understanding of social phenomena. Although a number of technical issues receive attention, the overall emphasis is on the larger historical, philosophical, and conceptual perspectives that underlie and inform current methodological controversies.
The debates in Causality in Crisis? have far-ranging implications, for on their resolution hinges the question of what sort of knowledge of social life it is possible to achieve on the basis of non-experimental social scientific research. Any scholar who makes use of causal methods, as well as all who are affected by decisions reached on the basis of such methods, will have a stake in the challenging arguments put forth in this volume.
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: Blossfeld, Hans-Peter Название: Causal Analysis with Event History Data Using Stata ISBN: 1032657782 ISBN-13(EAN): 9781032657783 Издательство: Taylor&Francis Рейтинг: Цена: 8267.00 р. 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: Carolyn R. Fawcett; S. Mehlberg; Paul Benacerraf; Название: Time, Causality, and the Quantum Theory ISBN: 9027707219 ISBN-13(EAN): 9789027707215 Издательство: Springer Рейтинг: Цена: 27251.00 р. 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: 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.
Автор: Daniels, Lisa Minot, Nicholas W. Название: Introduction to statistics and data analysis using stata (r) ISBN: 1506371833 ISBN-13(EAN): 9781506371832 Издательство: Sage Publications Рейтинг: Цена: 18058.00 р. Наличие на складе: Поставка под заказ.
Описание: Offering a step-by-step introduction to data analysis in Stata, this text uses examples from a variety of disciplines and extensive detail on the commands in stata.
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