Causal Analysis in Biomedicine and Epidemiology PDF Download
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Author: Mikel Aickin
Publisher: CRC Press
ISBN: 9780824707484
Category : Mathematics
Languages : en
Pages : 240
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Book Description
"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."
Author: Mikel Aickin
Publisher: CRC Press
ISBN: 9780824707484
Category : Mathematics
Languages : en
Pages : 240
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Book Description
"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."
Author: Olaf Dammann
Publisher: Springer
ISBN: 3319963074
Category : Medical
Languages : en
Pages : 139
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Book Description
Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
Author: Daniel Westreich
Publisher: Oxford University Press, USA
ISBN: 0190665769
Category : Medical
Languages : en
Pages : 241
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Book Description
A (LONG OVERDUE) CAUSAL APPROACH TO INTRODUCTORY EPIDEMIOLOGY Epidemiology is recognized as the science of public health, evidence-based medicine, and comparative effectiveness research. Causal inference is the theoretical foundation underlying all of the above. No introduction to epidemiology is complete without extensive discussion of causal inference; what's missing is a textbook that takes such an approach. Epidemiology by Design takes a causal approach to the foundations of traditional introductory epidemiology. Through an organizing principle of study designs, it teaches epidemiology through modern causal inference approaches, including potential outcomes, counterfactuals, and causal identification conditions. Coverage in this textbook includes: · Introduction to measures of prevalence and incidence (survival curves, risks, rates, odds) and measures of contrast (differences, ratios); the fundamentals of causal inference; and principles of diagnostic testing, screening, and surveillance · Description of three key study designs through the lens of causal inference: randomized trials, prospective observational cohort studies, and case-control studies · Discussion of internal validity (within a sample), external validity, and population impact: the foundations of an epidemiologic approach to implementation science For first-year graduate students and advanced undergraduates in epidemiology and public health fields more broadly, Epidemiology by Design offers a rigorous foundation in epidemiologic methods and an introduction to methods and thinking in causal inference. This new textbook will serve as a foundation not just for further study of the field, but as a head start on where the field is going.
Author: J. Mark Elwood
Publisher: Oxford University Press, USA
ISBN:
Category : Language Arts & Disciplines
Languages : en
Pages : 352
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Book Description
This book shows that in most controversial questions in medicine the essential argument concerns whether the available evidence supports a particular cause-and-effect relationship. Making this evaluation, however, requires a degree of critical thinking that is not emphasized in medical education. In redressing this imbalance, the author demonstrates that by defining the postulated causal relationship, the possible causal and non-causal explanations can be considered in a logical and constructive manner. Elwood assumes no preliminary knowledge, but starts from a simple logical base to lead the reader through types of studies which are relevant, including the issue of selection in subjects, bias in observations, influences of other factors, and statistical analysis. This yields a question and answer approach that can be applied to a wide range of clinical and epidemiological issues.
Author: Michael B. Bracken
Publisher: Yale University Press
ISBN: 0300188846
Category : Medical
Languages : en
Pages : 346
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Book Description
DIVA noted clinical epidemiologist shows how evidence-based medicine can help us understand and assess news about health risks, cures, and treatment “breakthroughs.�/div
Author: Mervyn Susser
Publisher:
ISBN:
Category : Medical
Languages : en
Pages : 208
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Book Description
Author: David A. Savitz
Publisher: Oxford University Press
ISBN: 0190243775
Category : Medical
Languages : en
Pages : 241
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Book Description
Evaluating the strength of epidemiologic evidence is inherently challenging, both for those new to the field and for experienced researchers. This book offers a strategy for assessing epidemiologic research findings, explicitly describing the goals and products of research
Author: Olaf Dammann
Publisher:
ISBN: 9783319963082
Category : Data mining
Languages : en
Pages : 134
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Book Description
Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
Author: Guido W. Imbens
Publisher: Cambridge University Press
ISBN: 0521885884
Category : Business & Economics
Languages : en
Pages : 647
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Book Description
This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
Author: Yu-Kang Tu
Publisher: Springer Science & Business Media
ISBN: 9400730241
Category : Medical
Languages : en
Pages : 315
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Book Description
Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology.
