Milton Terris1
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
Two Principles of Evidence and Their Implications for the Philosophy of Scientific Method
TWO PRINCIPLES OF EVIDENCE AND THEIR IMPLICATIONS FOR THE PHILOSOPHY OF SCIENTIFIC METHOD by Gregory Stephen Gandenberger BA, Philosophy, Washington University in St. Louis, 2009 MA, Statistics, University of Pittsburgh, 2014 Submitted to the Graduate Faculty of the Kenneth P. Dietrich School of Arts and Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2015 UNIVERSITY OF PITTSBURGH KENNETH P. DIETRICH SCHOOL OF ARTS AND SCIENCES This dissertation was presented by Gregory Stephen Gandenberger It was defended on April 14, 2015 and approved by Edouard Machery, Pittsburgh, Dietrich School of Arts and Sciences Satish Iyengar, Pittsburgh, Dietrich School of Arts and Sciences John Norton, Pittsburgh, Dietrich School of Arts and Sciences Teddy Seidenfeld, Carnegie Mellon University, Dietrich College of Humanities & Social Sciences James Woodward, Pittsburgh, Dietrich School of Arts and Sciences Dissertation Director: Edouard Machery, Pittsburgh, Dietrich School of Arts and Sciences ii Copyright © by Gregory Stephen Gandenberger 2015 iii TWO PRINCIPLES OF EVIDENCE AND THEIR IMPLICATIONS FOR THE PHILOSOPHY OF SCIENTIFIC METHOD Gregory Stephen Gandenberger, PhD University of Pittsburgh, 2015 The notion of evidence is of great importance, but there are substantial disagreements about how it should be understood. One major locus of disagreement is the Likelihood Principle, which says roughly that an observation supports a hypothesis to the extent that the hy- pothesis predicts it. The Likelihood Principle is supported by axiomatic arguments, but the frequentist methods that are most commonly used in science violate it. This dissertation advances debates about the Likelihood Principle, its near-corollary the Law of Likelihood, and related questions about statistical practice. -
The Magic of Randomization Versus the Myth of Real-World Evidence
The new england journal of medicine Sounding Board The Magic of Randomization versus the Myth of Real-World Evidence Rory Collins, F.R.S., Louise Bowman, M.D., F.R.C.P., Martin Landray, Ph.D., F.R.C.P., and Richard Peto, F.R.S. Nonrandomized observational analyses of large safety and efficacy because the potential biases electronic patient databases are being promoted with respect to both can be appreciable. For ex- as an alternative to randomized clinical trials as ample, the treatment that is being assessed may a source of “real-world evidence” about the effi- well have been provided more or less often to cacy and safety of new and existing treatments.1-3 patients who had an increased or decreased risk For drugs or procedures that are already being of various health outcomes. Indeed, that is what used widely, such observational studies may in- would be expected in medical practice, since both volve exposure of large numbers of patients. the severity of the disease being treated and the Consequently, they have the potential to detect presence of other conditions may well affect the rare adverse effects that cannot plausibly be at- choice of treatment (often in ways that cannot be tributed to bias, generally because the relative reliably quantified). Even when associations of risk is large (e.g., Reye’s syndrome associated various health outcomes with a particular treat- with the use of aspirin, or rhabdomyolysis as- ment remain statistically significant after adjust- sociated with the use of statin therapy).4 Non- ment for all the known differences between pa- randomized clinical observation may also suf- tients who received it and those who did not fice to detect large beneficial effects when good receive it, these adjusted associations may still outcomes would not otherwise be expected (e.g., reflect residual confounding because of differ- control of diabetic ketoacidosis with insulin treat- ences in factors that were assessed only incom- ment, or the rapid shrinking of tumors with pletely or not at all (and therefore could not be chemotherapy). -
A Unit-Error Theory for Register-Based Household Statistics
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Zhang, Li-Chun Working Paper A unit-error theory for register-based household statistics Discussion Papers, No. 598 Provided in Cooperation with: Research Department, Statistics Norway, Oslo Suggested Citation: Zhang, Li-Chun (2009) : A unit-error theory for register-based household statistics, Discussion Papers, No. 598, Statistics Norway, Research Department, Oslo This Version is available at: http://hdl.handle.net/10419/192580 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten Nutzungsrechte. may exercise further usage rights as specified in the indicated licence. www.econstor.eu Discussion Papers No. 598, December 2009 Statistics Norway, Statistical Methods and Standards Li-Chun Zhang A unit-error theory for register- based household statistics Abstract: The next round of census will be completely register-based in all the Nordic countries. -
(Meta-Analyses of Observational Studies in Epidemiology) Checklist
MOOSE (Meta-analyses Of Observational Studies in Epidemiology) Checklist A reporting checklist for Authors, Editors, and Reviewers of Meta-analyses of Observational Studies. You must report the page number in your manuscript where you consider each of the items listed in this checklist. If you have not included this information, either revise your manuscript accordingly before submitting or note N/A. Reporting Criteria Reported (Yes/No) Reported on Page No. Reporting of Background Problem definition Hypothesis statement Description of Study Outcome(s) Type of exposure or intervention used Type of study design used Study population Reporting of Search Strategy Qualifications of searchers (eg, librarians and investigators) Search strategy, including time period included in the synthesis and keywords Effort to include all available studies, including contact with authors Databases and registries searched Search software used, name and version, including special features used (eg, explosion) Use of hand searching (eg, reference lists of obtained articles) List of citations located and those excluded, including justification Method for addressing articles published in languages other than English Method of handling abstracts and unpublished studies Description of any contact with authors Reporting of Methods Description of relevance or appropriateness of studies assembled for assessing the hypothesis to be tested Rationale for the selection and coding of data (eg, sound clinical principles or convenience) Documentation of how data were classified -
Evolution of Clinical Trials Throughout History
Evolution of clinical trials throughout history Emma M. Nellhaus1, Todd H. Davies, PhD1 Author Affiliations: 1. Office of Research and Graduate Education, Marshall University Joan C. Edwards School of Medicine, Huntington, West Virginia The authors have no financial disclosures to declare and no conflicts of interest to report. Corresponding Author: Todd H. Davies, PhD Director of Research Development and Translation Marshall University Joan C. Edwards School of Medicine Huntington, West Virginia Email: [email protected] Abstract The history of clinical research accounts for the high ethical, scientific, and regulatory standards represented in current practice. In this review, we aim to describe the advances that grew from failures and provide a comprehensive view of how the current gold standard of clinical practice was born. This discussion of the evolution of clinical trials considers the length of time and efforts that were made in order to designate the primary objective, which is providing improved care for our patients. A gradual, historic progression of scientific methods such as comparison of interventions, randomization, blinding, and placebos in clinical trials demonstrates how these techniques are collectively responsible for a continuous advancement of clinical care. Developments over the years have been ethical as well as clinical. The Belmont Report, which many investigators lack appreciation for due to time constraints, represents the pinnacle of ethical standards and was developed due to significant misconduct. Understanding the history of clinical research may help investigators value the responsibility of conducting human subjects’ research. Keywords Clinical Trials, Clinical Research, History, Belmont Report In modern medicine, the clinical trial is the gold standard and most dominant form of clinical research. -
Quasi-Experimental Studies in the Fields of Infection Control and Antibiotic Resistance, Ten Years Later: a Systematic Review
HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Infect Control Manuscript Author Hosp Epidemiol Manuscript Author . Author manuscript; available in PMC 2019 November 12. Published in final edited form as: Infect Control Hosp Epidemiol. 2018 February ; 39(2): 170–176. doi:10.1017/ice.2017.296. Quasi-experimental Studies in the Fields of Infection Control and Antibiotic Resistance, Ten Years Later: A Systematic Review Rotana Alsaggaf, MS, Lyndsay M. O’Hara, PhD, MPH, Kristen A. Stafford, PhD, MPH, Surbhi Leekha, MBBS, MPH, Anthony D. Harris, MD, MPH, CDC Prevention Epicenters Program Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland. Abstract OBJECTIVE.—A systematic review of quasi-experimental studies in the field of infectious diseases was published in 2005. The aim of this study was to assess improvements in the design and reporting of quasi-experiments 10 years after the initial review. We also aimed to report the statistical methods used to analyze quasi-experimental data. DESIGN.—Systematic review of articles published from January 1, 2013, to December 31, 2014, in 4 major infectious disease journals. METHODS.—Quasi-experimental studies focused on infection control and antibiotic resistance were identified and classified based on 4 criteria: (1) type of quasi-experimental design used, (2) justification of the use of the design, (3) use of correct nomenclature to describe the design, and (4) statistical methods used. RESULTS.—Of 2,600 articles, 173 (7%) featured a quasi-experimental design, compared to 73 of 2,320 articles (3%) in the previous review (P<.01). Moreover, 21 articles (12%) utilized a study design with a control group; 6 (3.5%) justified the use of a quasi-experimental design; and 68 (39%) identified their design using the correct nomenclature. -
Epidemiology and Biostatistics (EPBI) 1
Epidemiology and Biostatistics (EPBI) 1 Epidemiology and Biostatistics (EPBI) Courses EPBI 2219. Biostatistics and Public Health. 3 Credit Hours. This course is designed to provide students with a solid background in applied biostatistics in the field of public health. Specifically, the course includes an introduction to the application of biostatistics and a discussion of key statistical tests. Appropriate techniques to measure the extent of disease, the development of disease, and comparisons between groups in terms of the extent and development of disease are discussed. Techniques for summarizing data collected in samples are presented along with limited discussion of probability theory. Procedures for estimation and hypothesis testing are presented for means, for proportions, and for comparisons of means and proportions in two or more groups. Multivariable statistical methods are introduced but not covered extensively in this undergraduate course. Public Health majors, minors or students studying in the Public Health concentration must complete this course with a C or better. Level Registration Restrictions: May not be enrolled in one of the following Levels: Graduate. Repeatability: This course may not be repeated for additional credits. EPBI 2301. Public Health without Borders. 3 Credit Hours. Public Health without Borders is a course that will introduce you to the world of disease detectives to solve public health challenges in glocal (i.e., global and local) communities. You will learn about conducting disease investigations to support public health actions relevant to affected populations. You will discover what it takes to become a field epidemiologist through hands-on activities focused on promoting health and preventing disease in diverse populations across the globe. -
U.S. Investments in Medical and Health Research and Development 2013 - 2017 Advocacy Has Helped Bring About Five Years of Much-Needed Growth in U.S
Fall 2018 U.S. Investments in Medical and Health Research and Development 2013 - 2017 Advocacy has helped bring about five years of much-needed growth in U.S. medical and health research investment. More advocacy is critical now to ensure our nation steps up in response to health threats that we can—we must—overcome. More Than Half Favor Doubling Federal Spending on Medical Research Do you favor or oppose doubling federal spending on medical research over the next five years? 19% Not Sure 23% 8% Strongly favor Strongly oppose 16% 35% Somewhat oppose Somewhat favor Source: A Research!America survey of U.S. adults conducted in partnership with Zogby Analytics in January 2018. Research!America 3 Introduction Investment1 in medical and health research and development (R&D) in the U.S. grew by $38.8 billion or 27% from 2013 to 2017. Industry continues to invest more than any other sector, accounting for 67% of total spending in 2017, followed by the federal government at 22%. Federal investments increased from 2016 to 2017, the second year of growth after a dip from 2014 to 2015. Overall, federal investment increased by $6.1 billion or 18.4% from 2013 to 2017, but growth has been uneven across federal health agencies. Investment by other sectors, including academic and research institutions, foundations, state and local governments, and voluntary health associations and professional societies, also increased from 2013 to 2017. Looking ahead, medical and health R&D spending is expected to move in an upward trajectory in 2018 but will continue to fall short relative to the health and economic impact of major health threats. -
Why Do We Need a Social Psychiatry? Antonio Ventriglio, Susham Gupta and Dinesh Bhugra
The British Journal of Psychiatry (2016) 209, 1–2. doi: 10.1192/bjp.bp.115.175349 Editorial Why do we need a social psychiatry? Antonio Ventriglio, Susham Gupta and Dinesh Bhugra Summary interventions in psychiatry should be considered in the Human beings are social animals, and familial or social framework of social context where patients live and factors relationships can cause a variety of difficulties as well as they face on a daily basis. providing support in our social functioning. The traditional way of looking at mental illness has focused on abnormal Declaration of interest thoughts, actions and behaviours in response to internal D.B. is President of the World Psychiatric Association. causes (such as biological factors) as well as external ones such as social determinants and social stressors. We Copyright and usage contend that psychiatry is social. Mental illness and B The Royal College of Psychiatrists 2016. and difficulties at these levels can lead to psychopathological Antonio Ventriglio (pictured) is an honorary researcher at the Department of and behavioural dysfunctions. Social stressors can lead to changes Clinical and Experimental Medicine at the University of Foggia, Italy. Susham 5 Gupta is a consultant psychiatrist at the East London Mental Health in the cerebral structure and affect neuro-hormonal pathways. Foundation NHS Trust. Dinesh Bhugra is Emeritus Professor of Mental Health Even organic conditions such as dementia are said to be related to & Cultural Diversity at the Institute of Psychiatry, Psychology & Neuroscience, life events and social factors such as economic and educational status.5 King’s College London and is President of the World Psychiatric Association. -
Clinical Research Services
Clinical Research Services Conducting efficient, innovative clinical research from initial planning to closeout WHY LEIDOS LIFE SCIENCES? In addition to developing large-scale technology programs for U.S. federal f Leidos has expertise agencies with a focus on health, Leidos provides a broad range of clinical supporting all product services and solutions to researchers, product sponsors, U.S. government development phases agencies, and other biomedical enterprises, hospitals, and health systems. for vaccines, drugs, and Our broad research experience enables us to support programs throughout biotherapeutics the development life cycle: from concept through the exploratory, f Leidos understands the development, pre-clinical, and clinical phases, as well as with product need to control clinical manufacturing and launching. Leidos designs and develops customized project scope, timelines, solutions that support groundbreaking medical research, optimize business and cost while remaining operations, and expedite the discovery of safe and effective medical flexible amidst shifting products. We apply our technical knowledge and experience in selecting research requirements institutions, clinical research organizations, and independent research f Leidos remains vendor- facilities to meet the specific needs of each clinical study. We also manage neutral while fostering and team integration, communication, and contracts throughout the project. managing collaborations Finally, Leidos has a proven track record of ensuring that research involving with -
Adaptive Designs in Clinical Trials: Why Use Them, and How to Run and Report Them Philip Pallmann1* , Alun W
Pallmann et al. BMC Medicine (2018) 16:29 https://doi.org/10.1186/s12916-018-1017-7 CORRESPONDENCE Open Access Adaptive designs in clinical trials: why use them, and how to run and report them Philip Pallmann1* , Alun W. Bedding2, Babak Choodari-Oskooei3, Munyaradzi Dimairo4,LauraFlight5, Lisa V. Hampson1,6, Jane Holmes7, Adrian P. Mander8, Lang’o Odondi7, Matthew R. Sydes3,SofíaS.Villar8, James M. S. Wason8,9, Christopher J. Weir10, Graham M. Wheeler8,11, Christina Yap12 and Thomas Jaki1 Abstract Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial’s course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented. We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. -
The Public’S Role in COVID-19 Vaccination
Vaccine xxx (xxxx) xxx Contents lists available at ScienceDirect Vaccine journal homepage: www.elsevier.com/locate/vaccine The public’s role in COVID-19 vaccination: Human-centered recommendations to enhance pandemic vaccine awareness, access, and acceptance in the United States ⇑ Monica Schoch-Spana a,c, , Emily K. Brunson b, Rex Long b, Alexandra Ruth c,f, Sanjana J. Ravi a,c, Marc Trotochaud a,c, Luciana Borio d, Janesse Brewer c, Joseph Buccina d, Nancy Connell a,c, Laura Lee Hall e, Nancy Kass c,f, Anna Kirkland g, Lisa Koonin h, Heidi Larson i, Brooke Fisher Lu j, Saad B. Omer k,l,m, Walter A. Orenstein n,o,p, Gregory A. Poland q, Lois Privor-Dumm r, Sandra Crouse Quinn s, Daniel Salmon c,t, Alexandre White u,v a Johns Hopkins Center for Health Security, Baltimore, MD, USA b Department of Anthropology, Texas State University, San Marcos, TX, USA c Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA d In-Q-Tel, Arlington, VA, USA e Center for Sustainable Health Care Quality and Equity, Washington, DC, USA f Johns Hopkins Berman Institute of Bioethics, Baltimore, MD, USA g Department of Women’s and Gender Studies, University of Michigan, Ann Arbor, MI, USA h Health Preparedness Partners, Atlanta, GA, USA i Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK j Department of Communication, University of Maryland, College Park, MD, USA k Yale Institute for Global Health, New Haven, CT, USA l Yale School of Medicine, New Haven, CT, USA m Yale School of Public Health,