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Causal Analysis in Biomedicine and Epidemiology

Provides current models, tools, and examples for the formulation and evaluation of scientific hypotheses in causal terms. Introduces a new;

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Causal Analysis in Biomedicine and Epidemiology

Provides current models, tools, and examples for the formulation and evaluation of scientific hypotheses in causal terms. Introduces a new;

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Modern Epidemiology

New chapters cover causal modeling: Bayesian analysis, probabilistic bias analysis, social epidemiology, and use of secondary data Includes;

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Epidemiology by Design

designs, it teaches epidemiology through modern causal inference approaches, including potential outcomes, counterfactuals, and causal;

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Modern Epidemiology

, validity, precision, statistical interference, field methods, and causal diagrams. Includes data analysis topics such as Bayesian analysis;

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Causality and Probability in the Sciences

its careful analysis, "Causality and Probability in the Sciences" heralds the transition of causal inference from an art to a science.;

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Exercises in Epidemiology

Traditional epidemiology coursework is centered on the design and analysis of disease control. This important knowledge forms the backbone;

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Concise Epidemiologic Principles and Concepts

-analysis) in causal inference. Epidemiology has evolved over the past three decades resulting in several fields being developed. This text presents;

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Direction Dependence in Statistical Modeling

incorporates the latest research for the statistical analysis of hypotheses that are compatible with the causal direction of dependence of variable;

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Epidemiology

introductory level. Epidemiology: An Introduction closes the gap. It begins with a brief, lucid discussion of casual thinking and causal inference and;

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Big Data in Omics and Imaging: Integrated Analysis and Causal Inference

Big Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic;

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Big Data in Omics and Imaging: Integrated Analysis and Causal Inference

Big Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic;

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Statistical Thinking in Epidemiology

: specific examples in epidemiology illustrate how different model specifications can imply different causal relationships amongst variables, and;

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Statistical Thinking in Epidemiology

: specific examples in epidemiology illustrate how different model specifications can imply different causal relationships amongst variables, and;

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Cerebral Palsies

work The Epidemiology of the Cerebral Palsies, and its focus is still on epidemiology. In Cerebral Palsies: Epidemiology and Causal Pathways;

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Practical Approaches to Causal Relationship Exploration

and decision making in medicine, epidemiology, biology, economics, physics and social sciences. The first two methods apply conditional;

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Statistics & Causality

analysis. Finally, the fifth part presents designs for causal inference with an overview of the research designs commonly used in epidemiology;

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Statistical Approaches to Causal Analysis

in action. McBee clearly demonstrates techniques such as Rubin causal model, direct acyclic graphs and propensity score analysis.;

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Methods in Social Epidemiology

rigorous investigation and analysis, while the general thinking in the field has become more targeted and attentive to causal inference and core;

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Handbook of Epidemiology

This 5-volume reference covers the entire field of epidemiology, from statistical methods and study design, to specialized areas such as;

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Psychiatric Epidemiology

attempting to review the descriptive epidemiology of mental disorders, this book gives a much more dynamic exposition of the thinking and techniques;

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Epidemiology Kept Simple

Epidemiology Kept Simple introduces the epidemiological principles and methods that are increasingly important in the practice of medicine;

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Causation in Population Health Informatics and Data Science

Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference;

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Modern Statistical Methods for Health Research

interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data;

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Big Data in Omics and Imaging, Two Volume Set

to Big Data in Omic and Imaging: Association Analysis, but can be read independently. Introduce causal inference;

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An Introduction to Causal Analysis in Sociology

An Introduction to Causal Analysis in Sociology is een boek van Ian Birnbaum;

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Epidemiology and Geography

practical introduction to spatial and spatio-temporal analysis for epidemiology and health geography, and takes an educational approach illustrated;

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