Causal Analysis with Event History Data Using Stata, Blossfeld, Hans-Peter
Старое издание
Автор: Blossfeld Название: Event History Analysis With Stata ISBN: 1138070858 ISBN-13(EAN): 9781138070851 Издательство: Taylor&Francis Цена: 51030 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: 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: 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: 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: 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: 45930.00 T Наличие на складе: Нет в наличии. 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: 60550.00 T 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.
Автор: Long, J. Scott (indiana University, Bloomington, Usa) Название: Workflow of data analysis using stata ISBN: 1597180475 ISBN-13(EAN): 9781597180474 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Невозможна поставка. Описание: Suitable for data analysts, this book demonstrates how to design and implement efficient workflows for both one-person projects and team projects. It describes planning, organizing, and documenting your work. It then introduces how to write and debug Stata do-files and how to use local and global macros.
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: 120390.00 T 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.
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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