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Causal Analysis in Biomedicine and Epidemiology, Aickin


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Цена: 33686.00р.
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Автор: Aickin
Название:  Causal Analysis in Biomedicine and Epidemiology
ISBN: 9780824707484
Издательство: Taylor&Francis
Классификация:


ISBN-10: 0824707486
Обложка/Формат: Hardback
Страницы: 236
Вес: 0.50 кг.
Дата издания: 09.11.2001
Язык: English
Размер: 236 x 159 x 18
Ключевые слова: Epidemiology, , Science
Основная тема: Medical Statistics & Computing
Подзаголовок: Based on minimal sufficient causation
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание: Provides current models, tools, and examples for the formulation and evaluation of scientific hypotheses in causal terms. Introduces a new method of model parametritization. Illustrates structural equations and graphical elements for complex causal systems.


Explanation in Causal Inference

Автор: VanderWeele Tyler
Название: Explanation in Causal Inference
ISBN: 0199325871 ISBN-13(EAN): 9780199325870
Издательство: Oxford Academ
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Цена: 18216.00 р.
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Описание: The book provides an accessible but comprehensive overview of methods for mediation and interaction. There has been considerable and rapid methodological development on mediation and moderation/interaction analysis within the causal-inference literature over the last ten years. Much of this
material appears in a variety of specialized journals, and some of the papers are quite technical. There has also been considerable interest in these developments from empirical researchers in the social and biomedical sciences. However, much of the material is not currently in a format that is
accessible to them. The book closes these gaps by providing an accessible, comprehensive, book-length coverage of mediation.

The book begins with a comprehensive introduction to mediation analysis, including chapters on concepts for mediation, regression-based methods, sensitivity analysis, time-to-event outcomes, methods for multiple mediators, methods for time-varying mediation and longitudinal data, and relations
between mediation and other concepts involving intermediates such as surrogates, principal stratification, instrumental variables, and Mendelian randomization. The second part of the book concerns interaction or "moderation," including concepts for interaction, statistical interaction, confounding
and interaction, mechanistic interaction, bias analysis for interaction, interaction in genetic studies, and power and sample-size calculation for interaction. The final part of the book provides comprehensive discussion about the relationships between mediation and interaction and unites these
concepts within a single framework. This final part also provides an introduction to spillover effects or social interaction, concluding with a discussion of social-network analyses.

The book is written to be accessible to anyone with a basic knowledge of statistics. Comprehensive appendices provide more technical details for the interested reader. Applied empirical examples from a variety of fields are given throughout. Software implementation in SAS, Stata, SPSS, and R is
provided. The book should be accessible to students and researchers who have completed a first-year graduate sequence in quantitative methods in one of the social- or biomedical-sciences disciplines. The book will only presuppose familiarity with linear and logistic regression, and could potentially
be used as an advanced undergraduate book as well.

Epidemiology: Study Design And Data Analysis

Автор: Mark Woodward
Название: Epidemiology: Study Design And Data Analysis
ISBN: 1439839700 ISBN-13(EAN): 9781439839706
Издательство: Taylor&Francis
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Цена: 13473.00 р.
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Описание:

Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems.

New to the Third Edition

  • New chapter on risk scores and clinical decision rules
  • New chapter on computer-intensive methods, including the bootstrap, permutation tests, and missing value imputation
  • New sections on binomial regression models, competing risk, information criteria, propensity scoring, and splines
  • Many more exercises and examples using both Stata and SAS
  • More than 60 new figures

After introducing study design and reviewing all the standard methods, this self-contained book takes students through analytical methods for both general and specific epidemiological study designs, including cohort, case-control, and intervention studies. In addition to classical methods, it now covers modern methods that exploit the enormous power of contemporary computers. The book also addresses the problem of determining the appropriate size for a study, discusses statistical modeling in epidemiology, covers methods for comparing and summarizing the evidence from several studies, and explains how to use statistical models in risk forecasting and assessing new biomarkers. The author illustrates the techniques with numerous real-world examples and interprets results in a practical way. He also includes an extensive list of references for further reading along with exercises to reinforce understanding.

Web Resource

A wealth of supporting material can be downloaded from the book's CRC Press web page, including:

  • Real-life data sets used in the text
  • SAS and Stata programs used for examples in the text
  • SAS and Stata programs for special techniques covered
  • Sample size spreadsheet
Mathematical Modeling of Biological Systems, Volume I Cellular Biophysics, Regulatory Networks, Development, Biomedicine, and Data Analysis

Автор: Deutsch, A.; Brusch, L.; Byrne, H.; de Vries, G.; Herzel, H. (Eds.)
Название: Mathematical Modeling of Biological Systems, Volume I Cellular Biophysics, Regulatory Networks, Development, Biomedicine, and Data Analysis
ISBN: 0817645578 ISBN-13(EAN): 9780817645571
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This edited volume contains a selection of chapters that are an outgrowth of the - ropean Conference on Mathematical and Theoretical Biology (ECMTB05, Dresden, Germany, July 2005). The peer-reviewed contributions show that mathematical and computational approaches are absolutely essential for solving central problems in the life sciences, ranging from the organizational level of individual cells to the dynamics of whole populations. The contributions indicate that theoretical and mathematical biology is a diverse and interdisciplinary ?eld, ranging from experimental research linked to mathema- cal modeling to the development of more abstract mathematical frameworks in which observations about the real world can be interpreted, and with which new hypotheses for testing can be generated. Today, much attention is also paid to the development of ef?cient algorithms for complex computation and visualisation, notably in molecular biology and genetics. The ?eld of theoretical and mathematical biology and medicine has profound connections to many current problems of great relevance to society. The medical, industrial, and social interests in its development are in fact indisputable.

Complex Systems in Biomedicine

Автор: Quarteroni
Название: Complex Systems in Biomedicine
ISBN: 8847003946 ISBN-13(EAN): 9788847003941
Издательство: Springer
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Цена: 18284.00 р.
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Описание: Mathematical modeling of human physiopathology is a tremendously ambitious task. It encompasses the modeling of most diverse compartments such as the cardiovascular, respiratory, skeletal and nervous systems, as well as the mechanical and biochemical interaction between blood flow and arterial walls, or electrocardiac processes and the electric conduction into biological tissues. Mathematical models can be set up to simulate both vasculogenesis (the aggregation and organisation of endothelial cells dispersed in a given environment) and angiogenesis (the formation of new vessels sprouting from an existing vessel) that are relevant to the formation of vascular networks, and in particular to the description of tumor growth. The integration of models aimed at simulating the cooperation and interrelation of different systems is an even more difficult task. It calls for the set up of, for instance, interaction models for the integrated cardio-vascular system and the interplay between central circulation and peripheral compartments, models for the mid-long range cardiovascular adjustments to pathological conditions (e.g. to account for surgical interventions, congenital malformations, or tumor growth), models for the integration among circulation, tissue perfusion, biochemical and thermal regulation, models for parameter identification and sensitivity analysis to parameter changes or data uncertainty – and many others. The heart is a complex system in itself, where electrical phenomena are functionally related with the wall deformation. In its turn, electrical activity is related with heart physiology. It involves nonlinear reaction-diffusion processes and provides the activation stimulus to the heart dynamics and eventually the blood ventricular flow that drives the haemodynamics of the whole circulatory system. In fact, the influence is reciprocal, since the circulatory system in turns affects the heart dynamics and may induce an overload depending upon the individual physiopathologies ( for instance the presence of a stenotic artery or a vascular prosthesis).Virtually, all the fields of mathematics have a role to play in this context. Geometry and approximation theory provide the tools for handling clinical data acquired by tomography or magnetic resonance, identifying meaningful geometrical patterns and producing three-dimensional geometrical models stemming from the original patients data. Mathematical analysis, flow and solid dynamics, stochastic analysis are used to set up the differential models and predict uncertainty. Numerical analysis and high performance computing are needed to numerically solve the complex differential models. Finally, methods from stochastic and statistical analysis are exploited for the modeling and interpretation of space-time patterns. Indeed, the complexity of the problems at hand often stimulates the use of innovative mathematical techniques that are able, for instance, to accurately catch those processes that occur at multiple scales in time and space (like cellular and systemic effects), and that are governed by heterogeneous physical laws.


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