Advertisement
| bias in cohort studies: Cohort Studies in Health Sciences R. Mauricio Barría, 2018 Introductory Chapter: The Contribution of Cohort Studies to Health Sciences. |
| bias in cohort studies: Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide Agency for Health Care Research and Quality (U.S.), 2013-02-21 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) |
| bias in cohort studies: Practical Psychiatric Epidemiology Jayati Das-Munshi, Tamsin Ford, Matthew Hotopf, Martin Prince, Robert Stewart, 2020-04-30 Epidemiology has been defined as the study of the distribution and determinants of health states or events in defined populations and its application to the control of health problems. Psychiatric epidemiology has continued to develop and apply these core principles in relation to mental health and mental disorders. This long-awaited second edition of Practical Psychiatric Epidemiology covers all of the considerable new developments in psychiatric epidemiology that have occurred since the first edition was published. It includes new content on key topics such as life course epidemiology, gene/environment interactions, bioethics, patient and public involvement in research, mixed methods research, new statistical methods, case registers, policy, and implementation. Looking to the future of this rapidly evolving scientific discipline and how it will to respond to the emerging opportunities and challenges posed by 'big data', new technologies, open science and globalisation, this new edition will continue to serve as an invaluable reference for clinicians in practice and in training. It will also be of interest to researchers in mental health and people studying or teaching psychiatric epidemiology at undergraduate or postgraduate level. |
| bias in cohort studies: Planning Clinical Research Robert A. Parker, Nancy G. Berman, 2016-10-12 Planning clinical research requires many decisions. The authors of this book explain key decisions with examples showing what works and what does not. |
| bias in cohort studies: Applying Quantitative Bias Analysis to Epidemiologic Data Timothy L. Lash, Matthew P. Fox, Aliza K. Fink, 2011-04-14 Bias analysis quantifies the influence of systematic error on an epidemiology study’s estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow. |
| bias in cohort studies: Handbook for Clinical Research Flora Hammond, MD, James F. Malec, Todd Nick, Ralph Buschbacher, MD, 2014-08-26 With over 80 information-packed chapters, Handbook for Clinical Research delivers the practical insights and expert tips necessary for successful research design, analysis, and implementation. Using clear language and an accessible bullet point format, the authors present the knowledge and expertise developed over time and traditionally shared from mentor to mentee and colleague to colleague. Organized for quick access to key topics and replete with practical examples, the book describes a variety of research designs and statistical methods and explains how to choose the best design for a particular project. Research implementation, including regulatory issues and grant writing, is also covered. The book opens with a section on the basics of research design, discussing the many ways in which studies can be organized, executed, and evaluated. The second section is devoted to statistics and explains how to choose the correct statistical approach and reviews the varieties of data types, descriptive and inferential statistics, methods for demonstrating associations, hypothesis testing and prediction, specialized methods, and considerations in epidemiological studies and measure construction. The third section covers implementation, including how to develop a grant application step by step, the project budget, and the nuts and bolts of the timely and successful completion of a research project and documentation of findings: procedural manuals and case report forms collecting, managing and securing data operational structure and ongoing monitoring and evaluation and ethical and regulatory concerns in research with human subjects. With a concise presentation of the essentials for successful research, the Handbook for Clinical Research is a valuable addition to the library of any student, research professional, or clinician interested in expanding the knowledge base of his or her field. Key Features: Delivers the essential elements, practical insights, and trade secrets for ensuring successful research design, analysis, and implementation Presents the nuts and bolts of statistical analysis Organized for quick access to a wealth of information Replete with practical examples of successful research designs Û from single case designs to meta-analysis - and how to achieve them Addresses research implementation including regulatory issues and grant writing |
| bias in cohort studies: Cochrane Handbook for Systematic Reviews of Interventions Julian P. T. Higgins, Sally Green, 2008-11-24 Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves. |
| bias in cohort studies: Epidemiology in Medicine Julie E. Buring, 1987 Harvard Medical School, Boston. Textbook for medical and public health students. |
| bias in cohort studies: Foundations of Epidemiology Marit L. Bovbjerg, 2020-10 Foundations of Epidemiology is an open access, introductory epidemiology text intended for students and practitioners in public or allied health fields. It covers epidemiologic thinking, causality, incidence and prevalence, public health surveillance, epidemiologic study designs and why we care about which one is used, measures of association, random error and bias, confounding and effect modification, and screening. Concepts are illustrated with numerous examples drawn from contemporary and historical public health issues. |
| bias in cohort studies: Critical Appraisal of Epidemiological Studies and Clinical Trials Mark Elwood, 2007-02-22 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. |
| bias in cohort studies: Concepts of Epidemiology Raj S. Bhopal, 2016 First edition published in 2002. Second edition published in 2008. |
| bias in cohort studies: Modern Epidemiology Kenneth J. Rothman, Sander Greenland, Timothy L. Lash, 2008 The thoroughly revised and updated Third Edition of the acclaimed Modern Epidemiology reflects both the conceptual development of this evolving science and the increasingly focal role that epidemiology plays in dealing with public health and medical problems. Coauthored by three leading epidemiologists, with sixteen additional contributors, this Third Edition is the most comprehensive and cohesive text on the principles and methods of epidemiologic research. The book covers a broad range of concepts and methods, such as basic measures of disease frequency and associations, study design, field methods, threats to validity, and assessing precision. It also covers advanced topics in data analysis such as Bayesian analysis, bias analysis, and hierarchical regression. Chapters examine specific areas of research such as disease surveillance, ecologic studies, social epidemiology, infectious disease epidemiology, genetic and molecular epidemiology, nutritional epidemiology, environmental epidemiology, reproductive epidemiology, and clinical epidemiology. |
| bias in cohort studies: Research in Medical and Biological Sciences Petter Laake, Haakon Breien Benestad, Bjorn R. Olsen, 2015-06-05 Research in Medical and Biological Sciences covers the wide range of topics that a researcher must be familiar with in order to become a successful biomedical scientist. Perfect for aspiring as well as practicing professionals in the medical and biological sciences, this publication discusses a broad range of topics that are common yet not traditionally considered part of formal curricula, including philosophy of science, ethics, statistics, and grant applications. The information presented in this book also facilitates communication across conventional disciplinary boundaries, in line with the increasingly multidisciplinary nature of modern research projects. - Covers the breadth of topics that a researcher must understand in order to be a successful experimental scientist - Provides a broad scientific perspective that is perfect for students with various professional backgrounds - Contains easily accessible, concise material about diverse methods - Includes extensive online resources such as further reading suggestions, data files, statistical tables, and the StaTable application package - Emphasizes the ethics and statistics of medical and biological sciences |
| bias in cohort studies: Biased Sampling, Over-identified Parameter Problems and Beyond Jing Qin, 2017-06-14 This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others. |
| bias in cohort studies: Principles of Research Design and Drug Literature Evaluation Rajender R. Aparasu, John P. Bentley, 2014-03-07 Principles of Research Design and Drug Literature Evaluation is a unique resource that provides a balanced approach covering critical elements of clinical research, biostatistical principles, and scientific literature evaluation techniques for evidence-based medicine. This accessible text provides comprehensive course content that meets and exceeds the curriculum standards set by the Accreditation Council for Pharmacy Education (ACPE). Written by expert authors specializing in pharmacy practice and research, this valuable text will provide pharmacy students and practitioners with a thorough understanding of the principles and practices of drug literature evaluation with a strong grounding in research and biostatistical principles. Principles of Research Design and Drug Literature Evaluation is an ideal foundation for professional pharmacy students and a key resource for pharmacy residents, research fellows, practitioners, and clinical researchers. FEATURES * Chapter Pedagogy: Learning Objectives, Review Questions, References, and Online Resources * Instructor Resources: PowerPoint Presentations, Test Bank, and an Answer Key * Student Resources: a Navigate Companion Website, including Crossword Puzzles, Interactive Flash Cards, Interactive Glossary, Matching Questions, and Web Links From the Foreword: This book was designed to provide and encourage practitioner’s development and use of critical drug information evaluation skills through a deeper understanding of the foundational principles of study design and statistical methods. Because guidance on how a study’s limited findings should not be used is rare, practitioners must understand and evaluate for themselves the veracity and implications of the inherently limited primary literature findings they use as sources of drug information to make evidence-based decisions together with their patients. The editors organized the book into three supporting sections to meet their pedagogical goals and address practitioners’ needs in translating research into practice. Thanks to the editors, authors, and content of this book, you can now be more prepared than ever before for translating research into practice. L. Douglas Ried, PhD, FAPhA Editor-in-Chief Emeritus, Journal of the American Pharmacists Association Professor and Associate Dean for Academic Affairs, College of Pharmacy, University of Texas at Tyler, Tyler, Texas |
| bias in cohort studies: Registries for Evaluating Patient Outcomes Agency for Healthcare Research and Quality/AHRQ, 2014-04-01 This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. 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. |
| bias in cohort studies: Finding What Works in Health Care Institute of Medicine, Board on Health Care Services, Committee on Standards for Systematic Reviews of Comparative Effectiveness Research, 2011-07-20 Healthcare decision makers in search of reliable information that compares health interventions increasingly turn to systematic reviews for the best summary of the evidence. Systematic reviews identify, select, assess, and synthesize the findings of similar but separate studies, and can help clarify what is known and not known about the potential benefits and harms of drugs, devices, and other healthcare services. Systematic reviews can be helpful for clinicians who want to integrate research findings into their daily practices, for patients to make well-informed choices about their own care, for professional medical societies and other organizations that develop clinical practice guidelines. Too often systematic reviews are of uncertain or poor quality. There are no universally accepted standards for developing systematic reviews leading to variability in how conflicts of interest and biases are handled, how evidence is appraised, and the overall scientific rigor of the process. In Finding What Works in Health Care the Institute of Medicine (IOM) recommends 21 standards for developing high-quality systematic reviews of comparative effectiveness research. The standards address the entire systematic review process from the initial steps of formulating the topic and building the review team to producing a detailed final report that synthesizes what the evidence shows and where knowledge gaps remain. Finding What Works in Health Care also proposes a framework for improving the quality of the science underpinning systematic reviews. This book will serve as a vital resource for both sponsors and producers of systematic reviews of comparative effectiveness research. |
| bias in cohort studies: Systematic Reviews in Health Care Matthias Egger, George Davey-Smith, Douglas Altman, 2008-04-15 The second edition of this best-selling book has been thoroughly revised and expanded to reflect the significant changes and advances made in systematic reviewing. New features include discussion on the rationale, meta-analyses of prognostic and diagnostic studies and software, and the use of systematic reviews in practice. |
| bias in cohort studies: Pediatric Board Study Guide Osama Naga, 2015-03-27 Covers the most frequently asked and tested points on the pediatric board exam. Each chapter offers a quick review of specific diseases and conditions clinicians need to know during the patient encounter. Easy-to-use and comprehensive, clinicians will find this guide to be the ideal final resource needed before taking the pediatric board exam. |
| bias in cohort studies: How to Practice Academic Medicine and Publish from Developing Countries? Samiran Nundy, Atul Kakar, Zulfiqar A. Bhutta, 2021-10-23 This is an open access book. The book provides an overview of the state of research in developing countries – Africa, Latin America, and Asia (especially India) and why research and publications are important in these regions. It addresses budding but struggling academics in low and middle-income countries. It is written mainly by senior colleagues who have experienced and recognized the challenges with design, documentation, and publication of health research in the developing world. The book includes short chapters providing insight into planning research at the undergraduate or postgraduate level, issues related to research ethics, and conduct of clinical trials. It also serves as a guide towards establishing a research question and research methodology. It covers important concepts such as writing a paper, the submission process, dealing with rejection and revisions, and covers additional topics such as planning lectures and presentations. The book will be useful for graduates, postgraduates, teachers as well as physicians and practitioners all over the developing world who are interested in academic medicine and wish to do medical research. |
| bias in cohort studies: Assessment of Cancer Screening Pamela M. Marcus, 2022 Cancer screening is a prominent strategy in cancer control in the United States, yet the ability to correctly interpret cancer screening data eludes many researchers, clinicians, and policy makers. This open access primer rectifies that situation by teaching readers, in simple language and with straightforward examples, why and how the population-level cancer burden changes when screening is implemented, and how we assess whether that change is of benefit. This book provides an in-depth look at the many aspects of cancer screening and its assessment, including screening phenomena, performance measures, population-level outcomes, research designs, and other important and timely topics. Concise, accessible, and focused, Assessment of Cancer Screening: A Primer is best suited to those with education or experience in clinical research or public health in the United States - no previous knowledge of cancer screening assessment is necessary. This is the first text dedicated to cancer screening theory and methodology to be published in 20 years. |
| bias in cohort studies: Age-Period-Cohort Analysis Yang Yang, Kenneth C. Land, 2016-04-19 This book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. They show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions. |
| bias in cohort studies: Randomized Controlled Trials Alehandro R. Jadad, Murray W. Enkin, 2007-07-23 Randomized controlled trials are one of the most powerful and revolutionary tools of research. This book is a convenient and accessible description of the underlying principles and practice of randomized controlled trials and their role in clinical decision-making. Structured in a jargon-free question-and-answer format, each chapter provides concise and understandable information on a different aspect of randomized controlled trials, from the basics of trial design and terminology to the interpretation of results and their use in driving evidence-based medicine. The authors end each chapter with their musings, going beyond the evidence or citations, and sometimes even beyond orthodox correctness to share their thoughts and concerns about different aspects of randomized controlled trials, and their role within the health system. Updated to include insights from the last decade, this second edition challenges over-reliance on randomized controlled trials by debating their strengths and limitations and discussing their optimal use in modern healthcare. It also includes a new and increasingly relevant chapter on the ethics of randomized trials. World renowned writers and thinkers Drs Jadad and Enkin bring you this invaluable book for busy health professionals who wish to understand the theory of randomized controlled trials and their influence on clinical, research or policy decisions. |
| bias in cohort studies: A Dictionary of Epidemiology Miquel S. Porta, Sander Greenland, Miguel Hernán, Isabel dos Santos Silva, John M. Last, 2014 This edition is the most updated since its inception, is the essential text for students and professionals working in and around epidemiology or using its methods. It covers subject areas - genetics, clinical epidemiology, public health practice/policy, preventive medicine, health promotion, social sciences and methods for clinical research. |
| bias in cohort studies: Secondary Analysis of Electronic Health Records MIT Critical Data, 2016-09-09 This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients. |
| bias in cohort studies: The Turnaway Study Diana Greene Foster, 2021-06 Now with a new afterword by the author--Back cover. |
| bias in cohort studies: Epidemiologic Research David G. Kleinbaum, Lawrence L. Kupper, Hal Morgenstern, 1991-01-16 Epidemiologic Research Principles and Quantitative Methods DavidG. Kleinbaum, Ph.D. Lawrence L. Kupper. Ph.D. Hal Morgenstern,Ph.D. Epidemiologic Research covers the principles and methodsof planning, analysis and interpretation of epidemiologic researchstudies. It supplies the applied researcher with the mostup-to-date methodological thought and practice. Specifically, thebook focuses on quantitative (including statistical) issues arisingfrom epidemiologic investigations, as well as on the questions ofstudy design, measurement and validity. EpidemiologicResearch emphasizes practical techniques, procedures andstrategies. It presents them through a unified approach whichfollows the chronology of issues that arise during theinvestigation of an epidemic. The book's viewpoint ismultidisciplinary and equally useful to the epidemiologicresearcher and to the biostatistician. Theory is supplemented bynumerous examples, exercises and applications. Full solutions aregiven to all exercises in a separate solutions manual. Importantfeatures * Thorough discussion of the methodology of epidemiologicresearch * Stress on validity and hence on reliability * Balanced approach, presenting the most important prevailingviewpoints * Three chapters with applications of mathematical modeling |
| bias in cohort studies: Analysis of Cancer Risks in Populations Near Nuclear Facilities National Research Council, Division on Earth and Life Studies, Nuclear and Radiation Studies Board, Committee on the Analysis of Cancer Risks in Populations near Nuclear Facilitiesâ¬"Phase I, 2012-06-29 In the late 1980s, the National Cancer Institute initiated an investigation of cancer risks in populations near 52 commercial nuclear power plants and 10 Department of Energy nuclear facilities (including research and nuclear weapons production facilities and one reprocessing plant) in the United States. The results of the NCI investigation were used a primary resource for communicating with the public about the cancer risks near the nuclear facilities. However, this study is now over 20 years old. The U.S. Nuclear Regulatory Commission requested that the National Academy of Sciences provide an updated assessment of cancer risks in populations near USNRC-licensed nuclear facilities that utilize or process uranium for the production of electricity. Analysis of Cancer Risks in Populations near Nuclear Facilities: Phase 1 focuses on identifying scientifically sound approaches for carrying out an assessment of cancer risks associated with living near a nuclear facility, judgments about the strengths and weaknesses of various statistical power, ability to assess potential confounding factors, possible biases, and required effort. The results from this Phase 1 study will be used to inform the design of cancer risk assessment, which will be carried out in Phase 2. This report is beneficial for the general public, communities near nuclear facilities, stakeholders, healthcare providers, policy makers, state and local officials, community leaders, and the media. |
| bias in cohort studies: Basic Methods Handbook for Clinical Orthopaedic Research Volker Musahl, Jón Karlsson, Michael T. Hirschmann, Olufemi R. Ayeni, Robert G. Marx, Jason L. Koh, Norimasa Nakamura, 2019-02-01 This book is designed to meet the needs of both novice and senior researchers in Orthopaedics by providing the essential, clinically relevant knowledge on research methodology that is sometimes overlooked during training. Readers will find a wealth of easy-to-understand information on all relevant aspects, from protocol design, the fundamentals of statistics, and the use of computer-based tools through to the performance of clinical studies with different levels of evidence, multicenter studies, systematic reviews, meta-analyses, and economic health care studies. A key feature is a series of typical case examples that will facilitate use of the volume as a handbook for most common research approaches and study types. Younger researchers will also appreciate the guidance on preparation of abstracts, poster and paper presentations, grant applications, and publications. The authors are internationally renowned orthopaedic surgeons with extensive research experience and the book is published in collaboration with ISAKOS. |
| bias in cohort studies: Good Research Practice in Non-Clinical Pharmacology and Biomedicine Anton Bespalov, Martin C. Michel, Thomas Steckler, 2020-01-01 This open access book, published under a CC BY 4.0 license in the Pubmed indexed book series Handbook of Experimental Pharmacology, provides up-to-date information on best practice to improve experimental design and quality of research in non-clinical pharmacology and biomedicine. |
| bias in cohort studies: Why Evolution is True Jerry A. Coyne, 2010-01-14 For all the discussion in the media about creationism and 'Intelligent Design', virtually nothing has been said about the evidence in question - the evidence for evolution by natural selection. Yet, as this succinct and important book shows, that evidence is vast, varied, and magnificent, and drawn from many disparate fields of science. The very latest research is uncovering a stream of evidence revealing evolution in action - from the actual observation of a species splitting into two, to new fossil discoveries, to the deciphering of the evidence stored in our genome. Why Evolution is True weaves together the many threads of modern work in genetics, palaeontology, geology, molecular biology, anatomy, and development to demonstrate the 'indelible stamp' of the processes first proposed by Darwin. It is a crisp, lucid, and accessible statement that will leave no one with an open mind in any doubt about the truth of evolution. |
| bias in cohort studies: Epidemiology and Health Services Haroutune K. Armenian, Sam Shapiro, 1998 What is the relevance of epidemiology to decision making in the health services? If our ability to launch large-scale experimental studies of health services is limited, what are some alternative approaches to study design? How can we best make use of routinely collected data from health information systems? How can we best synthesize information to make more reasonable inferences? Epidemiology and Health Services is different from other books in the field. Many books and specialized publications have presented a comprehensive picture of epidemiologic methods, but they have not shown in a systematic way how these methods apply to health services. This book fills the gap, and goes even further by analyzing the strengths and limitations of epidemiologic methods in the context of health care delivery, and discussing approaches for making pertinent inferences in actual cases. The book addresses the needs of a broad spectrum of health professionals. It will help health service administrators, managers and other professionals design and conduct evaluative and intervention research on the delivery of health services. It will also give epidemiology and public health students a wider perspective on the various applications of the discipline. |
| bias in cohort studies: Health Risks from Exposure to Low Levels of Ionizing Radiation Committee to Assess Health Risks from Exposure to Low Levels of Ionizing Radiation, National Research Council, 2006-03-23 This book is the seventh in a series of titles from the National Research Council that addresses the effects of exposure to low dose LET (Linear Energy Transfer) ionizing radiation and human health. Updating information previously presented in the 1990 publication, Health Effects of Exposure to Low Levels of Ionizing Radiation: BEIR V, this book draws upon new data in both epidemiologic and experimental research. Ionizing radiation arises from both natural and man-made sources and at very high doses can produce damaging effects in human tissue that can be evident within days after exposure. However, it is the low-dose exposures that are the focus of this book. So-called “late” effects, such as cancer, are produced many years after the initial exposure. This book is among the first of its kind to include detailed risk estimates for cancer incidence in addition to cancer mortality. BEIR VII offers a full review of the available biological, biophysical, and epidemiological literature since the last BEIR report on the subject and develops the most up-to-date and comprehensive risk estimates for cancer and other health effects from exposure to low-level ionizing radiation. |
| bias in cohort studies: Handbook of Life Course Health Development Neal Halfon, Christopher B. Forrest, Richard M. Lerner, Elaine M. Faustman, 2017-11-20 This book is open access under a CC BY 4.0 license. This handbook synthesizes and analyzes the growing knowledge base on life course health development (LCHD) from the prenatal period through emerging adulthood, with implications for clinical practice and public health. It presents LCHD as an innovative field with a sound theoretical framework for understanding wellness and disease from a lifespan perspective, replacing previous medical, biopsychosocial, and early genomic models of health. Interdisciplinary chapters discuss major health concerns (diabetes, obesity), important less-studied conditions (hearing, kidney health), and large-scale issues (nutrition, adversity) from a lifespan viewpoint. In addition, chapters address methodological approaches and challenges by analyzing existing measures, studies, and surveys. The book concludes with the editors’ research agenda that proposes priorities for future LCHD research and its application to health care practice and health policy. Topics featured in the Handbook include: The prenatal period and its effect on child obesity and metabolic outcomes. Pregnancy complications and their effect on women’s cardiovascular health. A multi-level approach for obesity prevention in children. Application of the LCHD framework to autism spectrum disorder. Socioeconomic disadvantage and its influence on health development across the lifespan. The importance of nutrition to optimal health development across the lifespan. The Handbook of Life Course Health Development is a must-have resource for researchers, clinicians/professionals, and graduate students in developmental psychology/science; maternal and child health; social work; health economics; educational policy and politics; and medical law as well as many interrelated subdisciplines in psychology, medicine, public health, mental health, education, social welfare, economics, sociology, and law. |
| bias in cohort studies: Encyclopedia of Pharmacy Practice and Clinical Pharmacy , 2019-06-28 Encyclopedia of Pharmacy Practice and Clinical Pharmacy, Three Volume Set covers definitions, concepts, methods, theories and applications of clinical pharmacy and pharmacy practice. It highlights why and how this field has a significant impact on healthcare. The work brings baseline knowledge, along with the latest, most cutting-edge research. In addition, new treatments, algorithms, standard treatment guidelines, and pharmacotherapies regarding diseases and disorders are also covered. The book's main focus lies on the pharmacy practice side, covering pharmacy practice research, pharmacovigilance, pharmacoeconomics, social and administrative pharmacy, public health pharmacy, pharmaceutical systems research, the future of pharmacy, and new interventional models of pharmaceutical care. By providing concise expositions on a broad range of topics, this book is an excellent resource for those seeking information beyond their specific areas of expertise. This outstanding reference is essential for anyone involved in the study of pharmacy practice. Provides a ‘one-stop’ resource for access to information written by world-leading scholars in the field Meticulously organized, with articles split into three clear sections, it is the ideal resource for students, researchers and professionals to find relevant information Contains concise and accessible chapters that are ideal as an authoritative introduction for non-specialists and readers from the undergraduate level upwards Includes multimedia options, such as hyperlinked references and further readings, cross-references and videos |
| bias in cohort studies: Validity and Inter-Rater Reliability Testing of Quality Assessment Instruments U. S. Department of Health and Human Services, Agency for Healthcare Research and Quality, 2013-04-09 The internal validity of a study reflects the extent to which the design and conduct of the study have prevented bias(es). One of the key steps in a systematic review is assessment of a study's internal validity, or potential for bias. This assessment serves to: (1) identify the strengths and limitations of the included studies; (2) investigate, and potentially explain heterogeneity in findings across different studies included in a systematic review; and (3) grade the strength of evidence for a given question. The risk of bias assessment directly informs one of four key domains considered when assessing the strength of evidence. With the increase in the number of published systematic reviews and development of systematic review methodology over the past 15 years, close attention has been paid to the methods for assessing internal validity. Until recently this has been referred to as “quality assessment” or “assessment of methodological quality.” In this context “quality” refers to “the confidence that the trial design, conduct, and analysis has minimized or avoided biases in its treatment comparisons.” To facilitate the assessment of methodological quality, a plethora of tools has emerged. Some of these tools were developed for specific study designs (e.g., randomized controlled trials (RCTs), cohort studies, case-control studies), while others were intended to be applied to a range of designs. The tools often incorporate characteristics that may be associated with bias; however, many tools also contain elements related to reporting (e.g., was the study population described) and design (e.g., was a sample size calculation performed) that are not related to bias. The Cochrane Collaboration recently developed a tool to assess the potential risk of bias in RCTs. The Risk of Bias (ROB) tool was developed to address some of the shortcomings of existing quality assessment instruments, including over-reliance on reporting rather than methods. Several systematic reviews have catalogued and critiqued the numerous tools available to assess methodological quality, or risk of bias of primary studies. In summary, few existing tools have undergone extensive inter-rater reliability or validity testing. Moreover, the focus of much of the tool development or testing that has been done has been on criterion or face validity. Therefore it is unknown whether, or to what extent, the summary assessments based on these tools differentiate between studies with biased and unbiased results (i.e., studies that may over- or underestimate treatment effects). There is a clear need for inter-rater reliability testing of different tools in order to enhance consistency in their application and interpretation across different systematic reviews. Further, validity testing is essential to ensure that the tools being used can identify studies with biased results. Finally, there is a need to determine inter-rater reliability and validity in order to support the uptake and use of individual tools that are recommended by the systematic review community, and specifically the ROB tool within the Evidence-based Practice Center (EPC) Program. In this project we focused on two tools that are commonly used in systematic reviews. The Cochrane ROB tool was designed for RCTs and is the instrument recommended by The Cochrane Collaboration for use in systematic reviews of RCTs. The Newcastle-Ottawa Scale is commonly used for nonrandomized studies, specifically cohort and case-control studies. |
| bias in cohort studies: Encyclopedia of Research Design Neil J. Salkind, 2010-06-22 Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases.--Publisher's description. |
| bias in cohort studies: Epidemiology Moyses Szklo, F. Javier Nieto, 2014 This book is specifically designed to expand reader knowledge while avoiding complex statistical formulations. Emphasizing the quantitative issues of epidemiology, this book focuses on study design, measures of association, interaction, research assessment, and other methods and practice. The Second Edition takes readers who have a good understanding of basic epidemiological principles through more rigorous discussions of concepts and methods. |
| bias in cohort studies: Methods in Social Epidemiology J. Michael Oakes, Jay S. Kaufman, 2006-05-11 Social epidemiology is the study of how social interactions—social norms, laws, institutions, conventia, social conditions and behavior—affect the health of populations. This practical, comprehensive introduction to methods in social epidemiology is written by experts in the field. It is perfectly timed for the growth in interest among those in public health, community health, preventive medicine, sociology, political science, social work, and other areas of social research. Topics covered are: Introduction: Advancing Methods in Social Epidemiology The History of Methods of Social Epidemilogy to 1965 Indicators of Socioeconomic Position Measuring and Analyzing 'Race' Racism and Racial Discrimination Measuring Poverty Measuring Health Inequalities A Conceptual Framework for Measuring Segregation and its Association with Population Outcomes Measures of Residential Community Contexts Using Census Data to Approximate Neighborhood Effects Community-based Participatory Research: Rationale and Relevance for Social Epidemiology Network Methods in Social Epidemiology Identifying Social Interactions: A Review, Multilevel Studies Experimental Social Epidemiology: Controlled Community Trials Propensity Score Matching Methods for Social Epidemiology Natural Experiments and Instrumental Variable Analyses in Social Epidemiology and Using Causal Diagrams to Understand Common Problems in Social Epidemiology. Publication of this highly informative textbook clearly reflects the coming of age of many social epidemiology methods, the importance of which rests on their potential contribution to significantly improving the effectiveness of the population-based approach to prevention. This book should be of great interest not only to more advanced epidemiology students but also to epidemiologists in general, particularly those concerned with health policy and the translation of epidemiologic findings into public health practice. The cause of achieving a ‘more complete’ epidemiology envisaged by the editors has been significantly advanced by this excellent textbook. —Moyses Szklo, professor of epidemiology and editor-in-chief, American Journal of Epidemiology, Johns Hopkins University Social epidemiology is a comparatively new field of inquiry that seeks to describe and explain the social and geographic distribution of health and of the determinants of health. This book considers the major methodological challenges facing this important field. Its chapters, written by experts in a variety of disciplines, are most often authoritative, typically provocative, and often debatable, but always worth reading. —Stephen W. Raudenbush, Lewis-Sebring Distinguished Service Professor, Department of Sociology, University of Chicago The roadmap for a new generation of social epidemiologists. The publication of this treatise is a significant event in the history of the discipline. —Ichiro Kawachi, professor of social epidemiology, Department of Society, Human Development, and Health, Harvard University Methods in Social Epidemiology not only illuminates the difficult questions that future generations of social epidemiologists must ask, it also identifies the paths they must boldly travel in the pursuit of answers, if this exciting interdisciplinary science is to realize its full potential. This beautifully edited volume appears at just the right moment to exert a profound influence on the field. —Sherman A. James, Susan B. King Professor of Public Policy Studies, professor of Community and Family Medicine, professor of African-American Studies, Duke University |
| bias in cohort studies: Practical Biostatistics Mendel Suchmacher, Mauro Geller, 2012-07-26 Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision making. It is a practice that uses statistical analysis of scientific methods and outcomes to drive further experimentation and diagnosis. The profusion of evidence-based medicine in medical practice and clinical research has produced a need for life scientists and clinical researchers to assimilate biostatistics into their work to meet efficacy and practical standards. Practical Biostatistics provides researchers, medical professionals, and students with a friendly, practical guide to biostatistics. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or a hands-on guide to effectively incorporate biostatistics in clinical trials. - Customized presentation for biological investigators with examples taken from current clinical trials in multiple disciplines - Clear and concise definitions and examples provide a pragmatic guide to bring clarity to the applications of statistics in improving human health - Addresses the challenge of assimilation of mathematical concepts to better interpret literature, to build stronger studies, to present research effectively, and to improve communication with supporting biostatisticians |
机器学习中的 Bias（偏差）、Error（误差）、Variance（方差）有 …
首先明确一点，Bias和Variance是针对Generalization（一般化，泛化）来说的。. 在机器学习中，我们用训练数据集去训练（学习）一个model（模型），通常的做法是定义一个Loss …
神经网络中的偏置（bias）究竟有什么用？ - 知乎
神经网络中的偏置（bias）究竟有什么用？ 最近写了一下模式识别的作业，简单的用python实现了一个三层神经网络，发现不加偏置的话，网络的训练精度一直不能够提升，加了偏执之后反而 …
偏差——bias与deviation的联系/区别？ - 知乎
各位同学，你们有没有想过‘偏见’在英语中是怎么说的？没错，答案就是'bias'！而且，我们这次还结合了一款超酷的桌面背单词软件，让你在学习单词的同时，也能感受到科技的魅
英文中prejudice和bias的区别? - 知乎
Bias：Bias is a tendency to prefer one person or thing to another, and to favour that person or thing. 可见 bias 所表示的意思是“偏爱”，其本质是一种喜好，而非厌恶，所以没有偏见的意思。
sci投稿Declaration of interest怎么写? - 知乎
正在写SCI的小伙伴看到这篇回答有福了！作为一个在硕士阶段发表了4篇SCI（一区×2，二区×2）的人，本回答就好好给你唠唠究竟该如何撰写Declaration of interest利益声明部分。
确认偏误是什么？如何系统地克服确认偏误？ - 知乎
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业 …
Linear classifier 里的 bias 有什么用？ - 知乎
Oct 27, 2015 · 你想象一下一维的情况，如果有两个点 -1 是负类， -2 是正类。如果没有bias，你的分类边界只能是过远点的一条垂直线，没法区分出这两个类别，bias给你提供了在特征空间上 …
选择性偏差（selection bias）指的是什么？ - 知乎
选择性偏差指的是在研究过程中因样本选择的非随机性而导致得到的结论存在偏差，包括自选择偏差（self-selection bias）和样本选择偏差（sample-selection bias）。消除选择性偏差，我们 …
哪里有标准的机器学习术语(翻译)对照表？ - 知乎
预测偏差 (prediction bias) 一种值，用于表明预测平均值与数据集中标签的平均值相差有多大。 预训练模型 (pre-trained model) 已经过训练的模型或模型组件（例如嵌套）。有时，您需要将预 …
如何理解Adam算法(Adaptive Moment Estimation)？ - 知乎
完整的Adam更新算法也包含了一个偏置（bias）矫正机制，因为m,v两个矩阵初始为0，在没有完全热身之前存在偏差，需要采取一些补偿措施。 不同最优化方法效果
机器学习中的 Bias（偏差）、Error（误差）、Variance（方差）有 …
首先明确一点，Bias和Variance是针对Generalization（一般化，泛化）来说的。. 在机器学习中，我们用训练数据集去训练（学习）一个model（模型），通常的做法是定义一个Loss …
神经网络中的偏置（bias）究竟有什么用？ - 知乎
神经网络中的偏置（bias）究竟有什么用？ 最近写了一下模式识别的作业，简单的用python实现了一个三层神经网络，发现不加偏置的话，网络的训练精度一直不能够提升，加了偏执之后反而 …
偏差——bias与deviation的联系/区别？ - 知乎
各位同学，你们有没有想过‘偏见’在英语中是怎么说的？没错，答案就是'bias'！而且，我们这次还结合了一款超酷的桌面背单词软件，让你在学习单词的同时，也能感受到科技的魅
英文中prejudice和bias的区别? - 知乎
Bias：Bias is a tendency to prefer one person or thing to another, and to favour that person or thing. 可见 bias 所表示的意思是“偏爱”，其本质是一种喜好，而非厌恶，所以没有偏见的意思。
sci投稿Declaration of interest怎么写? - 知乎
正在写SCI的小伙伴看到这篇回答有福了！作为一个在硕士阶段发表了4篇SCI（一区×2，二区×2）的人，本回答就好好给你唠唠究竟该如何撰写Declaration of interest利益声明部分。
确认偏误是什么？如何系统地克服确认偏误？ - 知乎
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业 …
Linear classifier 里的 bias 有什么用？ - 知乎
Oct 27, 2015 · 你想象一下一维的情况，如果有两个点 -1 是负类， -2 是正类。如果没有bias，你的分类边界只能是过远点的一条垂直线，没法区分出这两个类别，bias给你提供了在特征空间上 …
选择性偏差（selection bias）指的是什么？ - 知乎
选择性偏差指的是在研究过程中因样本选择的非随机性而导致得到的结论存在偏差，包括自选择偏差（self-selection bias）和样本选择偏差（sample-selection bias）。消除选择性偏差，我们 …
哪里有标准的机器学习术语(翻译)对照表？ - 知乎
预测偏差 (prediction bias) 一种值，用于表明预测平均值与数据集中标签的平均值相差有多大。 预训练模型 (pre-trained model) 已经过训练的模型或模型组件（例如嵌套）。有时，您需要将预 …
如何理解Adam算法(Adaptive Moment Estimation)？ - 知乎
完整的Adam更新算法也包含了一个偏置（bias）矫正机制，因为m,v两个矩阵初始为0，在没有完全热身之前存在偏差，需要采取一些补偿措施。 不同最优化方法效果
