Causal Inference for Competing Risks and Semi-competing Risks Data

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Publisher :
ISBN 13 :
Total Pages : 135 pages
Book Rating : 4.:/5 (133 download)

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Book Synopsis Causal Inference for Competing Risks and Semi-competing Risks Data by : Yiran Zhang

Download or read book Causal Inference for Competing Risks and Semi-competing Risks Data written by Yiran Zhang and published by . This book was released on 2022 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we utilize the novel statistical methods for obtaining causal effect under competing risks and semi-competing risks data in survival analysis. This dissertation is comprised of three main settings. In the first setting, we aim to assess the causal effect of mid-life alcohol exposure to the late life cognitive score which is related to Alzheimer's disease (AD) using a large scale longitudinal data. We applied the marginal structural model (MSM) with inverse probability weighted (IPW) to adjust for time-varying confounding. We found that there is a significant decline in cognitive scores among heavy drinkers compared always light drinker. However, since the cognitive scores also changes over time, learning the relationship of alcohol exposure and time to cognitive impairment is also worth to explore. In the second setting, we are interested in mid-life alcohol exposure to late life time to cognitive impairment which is also related to AD. Under this setting, as people are in their late-life stage, death prevents us from observing cognitive impairment. In survival analysis, death is considering as competing event. To estimate the causal effect of point treatment to time to event with the existence of competing event, we applied the MSM Cox proportional hazards model with IPW. Since hazard ratio is hard to interpret in medical research, we proposed predicted risk contrasts formula under the MSM Cox model. Observing the trend that people die quickly after experiencing cognitive impairment, in the third settings, we proposed a MSM illness-death to assess the causal effect for alcohol exposure to time to cognitive impairment, death and death after cognitive impairment. We considered two specific such models, the usual Markov illness-death structural model and the general Markov illness-death structural model which incorporates a frailty term. For interpretation purposes, risk contrasts under the structural models are defined. To accommodate the possibility of misspecification of propensity score model, we also derived the augmented IPW estimator under MSM illness-death usual Markov model.

Separable Effects for Causal Inference in the Presence of Competing Risks

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (115 download)

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Book Synopsis Separable Effects for Causal Inference in the Presence of Competing Risks by : Mats J. Stensrud

Download or read book Separable Effects for Causal Inference in the Presence of Competing Risks written by Mats J. Stensrud and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Competing Risks

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Publisher : John Wiley & Sons
ISBN 13 : 0470870699
Total Pages : 240 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Competing Risks by : Melania Pintilie

Download or read book Competing Risks written by Melania Pintilie and published by John Wiley & Sons. This book was released on 2006-11-02 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: The need to understand, interpret and analyse competing risk data is key to many areas of science, particularly medical research. There is a real need for a book that presents an overview of methodology used in the interpretation and analysis of competing risks, with a focus on practical applications to medical problems, and incorporating modern techniques. This book fills that need by presenting the most up-to-date methodology, in a way that can be readily understood, and applied, by the practitioner.

Competing Risks and Multistate Models with R

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Publisher : Springer Science & Business Media
ISBN 13 : 1461420350
Total Pages : 249 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Competing Risks and Multistate Models with R by : Jan Beyersmann

Download or read book Competing Risks and Multistate Models with R written by Jan Beyersmann and published by Springer Science & Business Media. This book was released on 2011-11-18 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.

A Dependent Competing Risks Model

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Publisher :
ISBN 13 : 9780438032262
Total Pages : 134 pages
Book Rating : 4.0/5 (322 download)

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Book Synopsis A Dependent Competing Risks Model by : Yiqing Wang

Download or read book A Dependent Competing Risks Model written by Yiqing Wang and published by . This book was released on 2018 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: The competing risks model considers the setting where subjects or units are exposed to multiple risks one of which may eventually cause the occurrence of the event, such as failure or recurrence or death. There is a substantial literature on identifiability and inference in both parametric and nonparametric models for competing risks. In this dissertation, we propose a parametric model for dependent competing risks that can be motivated by a frailty approach as well as by a copula approach. We establish identifiability conditions for this proposed model. We also consider competing risks regression framework and establish identifiability and methods for statistical inference in this framework. This proposed model has been further extended to analysis of semi-competing data while we again establish identifiability and statistical inference. The proposed models have been illustrated in extensive simulation studies and we apply these models to analyze competing risks data from a Tamoxifen trial on breast cancer patients and to analyze semi-competing risks data from a trial on tuberculous pericarditis collected in eight countries in Africa.

Classical Competing Risks

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Publisher : CRC Press
ISBN 13 : 1420035908
Total Pages : 201 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Classical Competing Risks by : Martin J. Crowder

Download or read book Classical Competing Risks written by Martin J. Crowder and published by CRC Press. This book was released on 2001-05-11 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: If something can fail, it can often fail in one of several ways and sometimes in more than one way at a time. There is always some cause of failure, and almost always, more than one possible cause. In one sense, then, survival analysis is a lost cause. The methods of Competing Risks have often been neglected in the survival analysis literature.

Data Analysis with Competing Risks and Intermediate States

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (126 download)

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Book Synopsis Data Analysis with Competing Risks and Intermediate States by : Ronald Geskus

Download or read book Data Analysis with Competing Risks and Intermediate States written by Ronald Geskus and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis with Competing Risks and Intermediate States explains when and how to use models and techniques for the analysis of competing risks and intermediate states. It covers the most recent insights on estimation techniques and discusses in detail how to interpret the obtained results. After introducing example studies from the biomedical and.

Bayesian Nonparametrics for Causal Inference and Missing Data

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Publisher : CRC Press
ISBN 13 : 1000927717
Total Pages : 263 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Bayesian Nonparametrics for Causal Inference and Missing Data by : Michael J. Daniels

Download or read book Bayesian Nonparametrics for Causal Inference and Missing Data written by Michael J. Daniels and published by CRC Press. This book was released on 2023-08-23 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest, such as missing at random assumption for missing data and unconfoundedness for causal inference in observational studies. Unlike parametric methods, the BNP approach can account for possible violations of assumptions and minimize concerns about model misspecification. The overall strategy is to first specify BNP models for observed data and then to specify additional uncheckable assumptions to identify estimands of interest. The book is divided into three parts. Part I develops the key concepts in causal inference and missing data and reviews relevant concepts in Bayesian inference. Part II introduces the fundamental BNP tools required to address causal inference and missing data problems. Part III shows how the BNP approach can be applied in a variety of case studies. The datasets in the case studies come from electronic health records data, survey data, cohort studies, and randomized clinical trials. Features • Thorough discussion of both BNP and its interplay with causal inference and missing data • How to use BNP and g-computation for causal inference and non-ignorable missingness • How to derive and calibrate sensitivity parameters to assess sensitivity to deviations from uncheckable causal and/or missingness assumptions • Detailed case studies illustrating the application of BNP methods to causal inference and missing data • R code and/or packages to implement BNP in causal inference and missing data problems The book is primarily aimed at researchers and graduate students from statistics and biostatistics. It will also serve as a useful practical reference for mathematically sophisticated epidemiologists and medical researchers.

The Frailty Model

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Publisher : Springer Science & Business Media
ISBN 13 : 038772835X
Total Pages : 329 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis The Frailty Model by : Luc Duchateau

Download or read book The Frailty Model written by Luc Duchateau and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.

Data Analysis with Competing Risks and Intermediate States

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Publisher : CRC Press
ISBN 13 : 1466570369
Total Pages : 278 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Data Analysis with Competing Risks and Intermediate States by : Ronald B. Geskus

Download or read book Data Analysis with Competing Risks and Intermediate States written by Ronald B. Geskus and published by CRC Press. This book was released on 2015-07-14 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis with Competing Risks and Intermediate States explains when and how to use models and techniques for the analysis of competing risks and intermediate states. It covers the most recent insights on estimation techniques and discusses in detail how to interpret the obtained results.After introducing example studies from the biomedical and

Targeted Learning

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Publisher : Springer Science & Business Media
ISBN 13 : 1441997822
Total Pages : 628 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Targeted Learning by : Mark J. van der Laan

Download or read book Targeted Learning written by Mark J. van der Laan and published by Springer Science & Business Media. This book was released on 2011-06-17 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands of measurements for a single subject. The field is ready to move towards clear objective benchmarks under which tools can be evaluated. Targeted learning allows (1) the full generalization and utilization of cross-validation as an estimator selection tool so that the subjective choices made by humans are now made by the machine, and (2) targeting the fitting of the probability distribution of the data toward the target parameter representing the scientific question of interest. This book is aimed at both statisticians and applied researchers interested in causal inference and general effect estimation for observational and experimental data. Part I is an accessible introduction to super learning and the targeted maximum likelihood estimator, including related concepts necessary to understand and apply these methods. Parts II-IX handle complex data structures and topics applied researchers will immediately recognize from their own research, including time-to-event outcomes, direct and indirect effects, positivity violations, case-control studies, censored data, longitudinal data, and genomic studies.

Frailty Models in Survival Analysis

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Publisher : CRC Press
ISBN 13 : 9781420073911
Total Pages : 324 pages
Book Rating : 4.0/5 (739 download)

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Book Synopsis Frailty Models in Survival Analysis by : Andreas Wienke

Download or read book Frailty Models in Survival Analysis written by Andreas Wienke and published by CRC Press. This book was released on 2010-07-26 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frailty Models in Survival Analysis presents a comprehensive overview of the fundamental approaches in the area of frailty models. The book extensively explores how univariate frailty models can represent unobserved heterogeneity. It also emphasizes correlated frailty models as extensions of univariate and shared frailty models. The author analyzes similarities and differences between frailty and copula models; discusses problems related to frailty models, such as tests for homogeneity; and describes parametric and semiparametric models using both frequentist and Bayesian approaches. He also shows how to apply the models to real data using the statistical packages of R, SAS, and Stata. The appendix provides the technical mathematical results used throughout. Written in nontechnical terms accessible to nonspecialists, this book explains the basic ideas in frailty modeling and statistical techniques, with a focus on real-world data application and interpretation of the results. By applying several models to the same data, it allows for the comparison of their advantages and limitations under varying model assumptions. The book also employs simulations to analyze the finite sample size performance of the models.

Targeted Learning in Data Science

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Publisher : Springer
ISBN 13 : 3319653040
Total Pages : 655 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Targeted Learning in Data Science by : Mark J. van der Laan

Download or read book Targeted Learning in Data Science written by Mark J. van der Laan and published by Springer. This book was released on 2018-03-28 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011. Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics. Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integrating innovative statistical approaches to advance human health. Dr. Rose’s methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.

Summary Measures of Population Health

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Publisher : World Health Organization
ISBN 13 : 9789241545518
Total Pages : 816 pages
Book Rating : 4.5/5 (455 download)

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Book Synopsis Summary Measures of Population Health by : World Health Organization

Download or read book Summary Measures of Population Health written by World Health Organization and published by World Health Organization. This book was released on 2002 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: As life expectancy rates continue to increase in many countries around the world, comparative health assessments based on mortality rates alone give an increasingly inadequate picture of public health. This publication addresses a wide range of key issues regarding the measurement of population health using comprehensive indices which combine data on mortality and ill-health. It considers the various uses of such summary measures, as well as an appropriate measurement framework and specific ethical and social value choices involved. The contributors to this book include leading experts in epidemiological methods, ethics, health economics, health status measurement and the valuation of health states.

Statistical Inference as Severe Testing

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Publisher : Cambridge University Press
ISBN 13 : 1108563309
Total Pages : 503 pages
Book Rating : 4.1/5 (85 download)

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Book Synopsis Statistical Inference as Severe Testing by : Deborah G. Mayo

Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

Handbook of Statistical Genomics

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Publisher : John Wiley & Sons
ISBN 13 : 1119429250
Total Pages : 1828 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Handbook of Statistical Genomics by : David J. Balding

Download or read book Handbook of Statistical Genomics written by David J. Balding and published by John Wiley & Sons. This book was released on 2019-07-09 with total page 1828 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.

Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide

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Publisher : Government Printing Office
ISBN 13 : 1587634236
Total Pages : 236 pages
Book Rating : 4.5/5 (876 download)

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Book Synopsis Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide by : Agency for Health Care Research and Quality (U.S.)

Download or read book Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide written by Agency for Health Care Research and Quality (U.S.) and published by Government Printing Office. This book was released on 2013-02-21 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)