Causal Inference For Case Control Studies
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Handbook Of Statistical Methods For Case Control Studies
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Author : Ørnulf Borgan
language : en
Publisher: CRC Press
Release Date : 2018-06-27
Handbook Of Statistical Methods For Case Control Studies written by Ørnulf Borgan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-27 with Mathematics categories.
Handbook of Statistical Methods for Case-Control Studies is written by leading researchers in the field. It provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, as well as a review of classical principles and methods. The handbook is designed to serve as a reference text for biostatisticians and quantitatively-oriented epidemiologists who are working on the design and analysis of case-control studies or on related statistical methods research. Though not specifically intended as a textbook, it may also be used as a backup reference text for graduate level courses. Book Sections Classical designs and causal inference, measurement error, power, and small-sample inference Designs that use full-cohort information Time-to-event data Genetic epidemiology About the Editors Ørnulf Borgan is Professor of Statistics, University of Oslo. His book with Andersen, Gill and Keiding on counting processes in survival analysis is a world classic. Norman E. Breslow was, at the time of his death, Professor Emeritus in Biostatistics, University of Washington. For decades, his book with Nick Day has been the authoritative text on case-control methodology. Nilanjan Chatterjee is Bloomberg Distinguished Professor, Johns Hopkins University. He leads a broad research program in statistical methods for modern large scale biomedical studies. Mitchell H. Gail is a Senior Investigator at the National Cancer Institute. His research includes modeling absolute risk of disease, intervention trials, and statistical methods for epidemiology. Alastair Scott was, at the time of his death, Professor Emeritus of Statistics, University of Auckland. He was a major contributor to using survey sampling methods for analyzing case-control data. Chris J. Wild is Professor of Statistics, University of Auckland. His research includes nonlinear regression and methods for fitting models to response-selective data.
Causal Inference For Case Control Studies
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Author : Sherri Rose
language : en
Publisher:
Release Date : 2011
Causal Inference For Case Control Studies written by Sherri Rose and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Case-control study designs are frequently used in public health and medical research to assess potential risk factors for disease. These study designs are particularly attractive to investigators researching rare diseases, as they are able to sample known cases of disease, vs. following a large number of subjects and waiting for disease onset in a relatively small number of individuals. The data-generating experiment in case-control study designs involves an additional complexity called biased sampling. That is, one assumes the underlying experiment that randomly samples a unit from a target population, measures baseline characteristics, assigns an exposure, and measures a final binary outcome, but one samples from the conditional probability distribution, given the value of the binary outcome. One still desires to assess the causal effect of exposure on the binary outcome for the target population. The targeted maximum likelihood estimator of a causal effect of treatment on the binary outcome based on such case-control studies is presented. Our proposed case-control-weighted targeted maximum likelihood estimator for case-control studies relies on knowledge of the true prevalence probability, or a reasonable estimate of this probability, to eliminate the bias of the case-control sampling design. We use the prevalence probability in case-control weights, and our case-control weighting scheme successfully maps the targeted maximum likelihood estimator for a random sample into a method for case-control sampling. Individually matched case-control study designs are commonly implemented in the field of public health. While matching is intended to eliminate confounding, the main potential benefit of matching in case-control studies is a gain in efficiency. We investigate the use of the case-control-weighted targeted maximum likelihood estimator to estimate causal effects in matched case-control study designs. We also compare the case-control-weighted targeted maximum likelihood estimator in matched and unmatched designs in an effort to determine which design yields the most information about the causal effect. In many practical situations where a causal effect is the parameter of interest, researchers may be better served using an unmatched design. We also consider two-stage sampling designs, including so-called nested case-control studies, where one takes a random sample from a target population and completes measurements on each subject in the first stage. The second stage involves drawing a subsample from the original sample, collecting additional data on the subsample. This data structure can be viewed as a missing data structure on the full-data structure collected in the second stage of the study. We propose an inverse-probability-of-censoring-weighted targeted maximum likelihood estimator in two-stage sampling designs. Two-stage designs are also common for prediction research questions. We present an analysis using super learner in nested case-control data from a large Kaiser Permanente database to generate a function for mortality risk prediction.
Handbook Of Statistical Methods For Case Control Studies
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Author : Ørnulf Borgan
language : en
Publisher: CRC Press
Release Date : 2020-06-30
Handbook Of Statistical Methods For Case Control Studies written by Ørnulf Borgan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-30 with categories.
This handbook provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, with a primary focus on case-control studies in epidemiology. Authors will be encouraged to illustrate the statistical methods they describe by application to datasets that are either alread
Causal Inference In Case Control Studies
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Author : Sung Jae Jun
language : en
Publisher:
Release Date : 2020
Causal Inference In Case Control Studies written by Sung Jae Jun and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
We investigate identification of causal parameters in case-control and related studies. The odds ratio in the sample is our main estimand of interest and we articulate its relationship with causal parameters under various scenarios. It turns out that the odds ratio is generally a sharp upper bound for counterfactual relative risk under some monotonicity assumptions, without resorting to strong ig-norability, nor to the rare-disease assumption. Further, we propose semparametrically efficient, easy-to-implement, machine-learning-friendly estimators of the aggregated (log) odds ratio by exploiting an explicit form of the efficient influence function. Using our new estimators, we develop methods for causal inference and illustrate the usefulness of our methods by a real-data example.
A Finite Population Approach For Causal Inference In Nested Case Control Studies
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Author : Katarina Majetic
language : en
Publisher:
Release Date : 2021
A Finite Population Approach For Causal Inference In Nested Case Control Studies written by Katarina Majetic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
"The nested case-control design is employed by researchers when it is too difficult or expensive to collect and/or analyze data prospectively on rare outcomes. The sampling design is retrospective in nature but the conclusions are prospective in nature, which can lead to bias when analyzed inappropriately. Most nested case-control approaches employ logistic regression, however, in this retrospective analysis, a difficulty arises when one wants to employ causal inference methods to adjust to time-varying confounding. In this thesis, we introduce methods that allow us to use prospective causal inference methods with time-varying confounding, under a retrospective nested case-control sub-sampling scheme which requires a different approach to the classic nested case-control design. We interpret the entire cohort data set as a fixed finite population, thus, when we take our nested case-control sample, it will be viewed as a draw from the finite population. In order to account for causal effects, we use inverse probability (IP) treatment weighting on top of the sampling weights. Thus, we introduce methods to solve a nested case-control problem using finite population methods in a causal setting"--
Oxford Textbook Of Global Public Health
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Author : Roger Detels
language : en
Publisher: Oxford University Press
Release Date : 2017
Oxford Textbook Of Global Public Health written by Roger Detels and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Medical categories.
Sixth edition of the hugely successful, internationally recognised textbook on global public health and epidemiology, with 3 volumes comprehensively covering the scope, methods, and practice of the discipline
Explanation In Causal Inference
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Author : Tyler J. VanderWeele
language : en
Publisher: Oxford University Press, USA
Release Date : 2015
Explanation In Causal Inference written by Tyler J. VanderWeele and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Mathematics categories.
A comprehensive examination of methods for mediation and interaction, VanderWeele's book is the first to approach this topic from the perspective of causal inference. Numerous software tools are provided, and the text is both accessible and easy to read, with examples drawn from diverse fields. The result is an essential reference for anyone conducting empirical research in the biomedical or social sciences.
Epidemiology By Design
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Author : Daniel Westreich
language : en
Publisher: Oxford University Press
Release Date : 2019-10-16
Epidemiology By Design written by Daniel Westreich and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-16 with Medical categories.
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.
Critical Appraisal Of Epidemiological Studies And Clinical Trials
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Author : Mark Elwood
language : en
Publisher: OUP Oxford
Release Date : 2007-02-22
Critical Appraisal Of Epidemiological Studies And Clinical Trials written by Mark Elwood and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-02-22 with Medical categories.
This book presents a logical system of critical appraisal, to allow readers to evaluate studies and to carry out their own studies more effectively. This system emphasizes the central importance of cause and effect relationships. Its great strength is that it is applicable to a wide range of issues, and both to intervention trials and observational studies. This system unifies the often different approaches used in epidemiology, health services research, clinical trials, and evidence-based medicine, starting from a logical consideration of cause and effect. The author's approach to the issues of study design, selection of subjects, bias, confounding, and the place of statistical methods has been praised for its clarity and interest. Systematic reviews, meta-analysis, and the applications of this logic to evidence-based medicine, knowledge-based health care, and health practice and policy are discussed. Current and often controversial examples are used, including screening for prostate cancer, publication bias in psychiatry, public health issues in developing countries, and conflicts between observational studies and randomized trials. Statistical issues are explained clearly without complex mathematics, and the most useful methods are summarized in the appendix. The final chapters give six applications of the critical appraisal of major studies: randomized trials of medical treatment and prevention, a prospective and a retrospective cohort study, a small matched case-control study, and a large case-control study. In these chapters, sections of the original papers are reproduced and the original studies placed in context by a summary of current developments.
Causal Inference And Case Control Studies With Applications Related To Childhood Diabetes
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Author :
language : en
Publisher:
Release Date : 2014
Causal Inference And Case Control Studies With Applications Related To Childhood Diabetes written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.