USING RESEARCH EVIDENCE a Practice Guide 1
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1 How to Make Experimental Economics
This article is © Emerald Group Publishing and permission has been granted for this version to appear here (http://eprints.nottingham.ac.uk/id/eprint/32996). Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited. How to Make Experimental Economics Research More Reproducible: Lessons from Other Disciplines and a New Proposal1 Zacharias Maniadis, University of Southampton Fabio Tufano, University of Nottingham John A. List University of Chicago2 Abstract: Efforts in the spirit of this special issue aim at improving the reproducibility of experimental economics, in response to the recent discussions regarding the “research reproducibility crisis.” We put this endeavour in perspective by summarizing the main ways (to our knowledge) that have been proposed – by researchers from several disciplines – to alleviate the problem. We discuss the scope for economic theory to contribute to evaluating the proposals. We argue that a potential key impediment to replication is the expectation of negative reactions by the authors of the individual study, and suggest that incentives for having one’s work replicated should increase. JEL Codes: B40, C90 Keywords: False-Positives, Reproducibility, Replication Introduction Nearly a century ago Ronald Fisher began laying the groundwork of experimental practice, which remains today. Fisher’s work was highlighted by the experimental tripod: the concepts of replication, blocking, and randomization were the foundation on which the analysis of the experiment was based. The current volume of Research in Experimental Economics (REE for short) aims at helping experimental economists think more deeply about replication, which has attracted the attention of scholars in other disciplines for some time. -
Cebm-Levels-Of-Evidence-Background-Document-2-1.Pdf
Background document Explanation of the 2011 Oxford Centre for Evidence-Based Medicine (OCEBM) Levels of Evidence Introduction The OCEBM Levels of Evidence was designed so that in addition to traditional critical appraisal, it can be used as a heuristic that clinicians and patients can use to answer clinical questions quickly and without resorting to pre-appraised sources. Heuristics are essentially rules of thumb that helps us make a decision in real environments, and are often as accurate as a more complicated decision process. A distinguishing feature is that the Levels cover the entire range of clinical questions, in the order (from top row to bottom row) that the clinician requires. While most ranking schemes consider strength of evidence for therapeutic effects and harms, the OCEBM system allows clinicians and patients to appraise evidence for prevalence, accuracy of diagnostic tests, prognosis, therapeutic effects, rare harms, common harms, and usefulness of (early) screening. Pre-appraised sources such as the Trip Database (1), (2), or REHAB+ (3) are useful because people who have the time and expertise to conduct systematic reviews of all the evidence design them. At the same time, clinicians, patients, and others may wish to keep some of the power over critical appraisal in their own hands. History Evidence ranking schemes have been used, and criticised, for decades (4-7), and each scheme is geared to answer different questions(8). Early evidence hierarchies(5, 6, 9) were introduced primarily to help clinicians and other researchers appraise the quality of evidence for therapeutic effects, while more recent attempts to assign levels to evidence have been designed to help systematic reviewers(8), or guideline developers(10). -
The Hierarchy of Evidence Pyramid
The Hierarchy of Evidence Pyramid Available from: https://www.researchgate.net/figure/Hierarchy-of-evidence-pyramid-The-pyramidal-shape-qualitatively-integrates-the- amount-of_fig1_311504831 [accessed 12 Dec, 2019] Available from: https://journals.lww.com/clinorthop/Fulltext/2003/08000/Hierarchy_of_Evidence__From_Case_Reports_to.4.aspx [accessed 14 March 2020] CLINICAL ORTHOPAEDICS AND RELATED RESEARCH Number 413, pp. 19–24 © 2003 Lippincott Williams & Wilkins, Inc. Hierarchy of Evidence: From Case Reports to Randomized Controlled Trials Brian Brighton, MD*; Mohit Bhandari, MD, MSc**; Downloaded from https://journals.lww.com/clinorthop by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3oaxD/v Paul Tornetta, III, MD†; and David T. Felson, MD* In the hierarchy of research designs, the results This hierarchy has not been supported in two re- of randomized controlled trials are considered cent publications in the New England Journal of the highest level of evidence. Randomization is Medicine which identified nonsignificant differ- the only method for controlling for known and ences in results between randomized, controlled unknown prognostic factors between two com- trials, and observational studies. The current au- parison groups. Lack of randomization predis- thors provide an approach to organizing pub- poses a study to potentially important imbal- lished research on the basis of study design, a hi- ances in baseline characteristics between two erarchy of evidence, a set of principles and tools study groups. There is a hierarchy of evidence, that help clinicians distinguish ignorance of evi- with randomized controlled trials at the top, con- dence from real scientific uncertainty, distin- trolled observational studies in the middle, and guish evidence from unsubstantiated opinions, uncontrolled studies and opinion at the bottom. -
Causality in Medicine with Particular Reference to the Viral Causation of Cancers
Causality in medicine with particular reference to the viral causation of cancers Brendan Owen Clarke A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy of UCL Department of Science and Technology Studies UCL August 20, 2010 Revised version January 24, 2011 I, Brendan Owen Clarke, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. ................................................................ January 24, 2011 2 Acknowledgements This thesis would not have been written without the support and inspiration of Donald Gillies, who not only supervised me, but also introduced me to history and philosophy of science in the first instance. I have been very privileged to be the beneficiary of so much of his clear thinking over the last few years. Donald: thank you for everything, and I hope this thesis lives up to your expectations. I am also extremely grateful to Michela Massimi, who has acted as my second supervisor. She has provided throughout remarkably insightful feedback on this project, no matter how distant it is from her own research interests. I’d also like to thank her for all her help and guidance on teaching matters. I should also thank Vladimir Vonka for supplying many important pieces of both the cervical cancer history, as well as his own work on causality in medicine from the perspective of a real, working medical researcher. Phyllis McKay-Illari provided a critical piece of the story, as well as many interesting and stim- ulating discussions about the more philosophical aspects of this thesis. -
(STROBE) Statement: Guidelines for Reporting Observational Studies
Policy and practice The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies* Erik von Elm,a Douglas G Altman,b Matthias Egger,a,c Stuart J Pocock,d Peter C Gøtzsche e & Jan P Vandenbroucke f for the STROBE Initiative Abstract Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study’s generalizability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control and cross-sectional studies. We convened a two-day workshop, in September 2004, with methodologists, researchers and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results and discussion sections of articles. Eighteen items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the web sites of PLoS Medicine, Annals of Internal Medicine and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies. -
Drug Information Associates
Drug Information Associates BRIEF: INFORMATION SERVICES IN AN ERA OF the use of new, expensive therapies (such as specialty UNPRECEDENTED EVIDENCE EXPANSION drugs, for example) be justified when compared to Heath Ford, PharmD, PhD | May 23, 2020 established practice?” In education, “can learners in certain outcome segments be expected to show Have you ever wondered … how effective is the statin improvement given new programs and substantial drug your doctor prescribed? Or the anti-depressant, increases in investment?” And in manufacturing, “are antipsychotic, or amphetamine? What about the recommended process improvements reasonable given expensive injectable medication your discount card or projected output expectations and investment costs?” drug coupon allows you to get every month for a low copay? And what about medical education (eg, medicine, These considerations validate the need for specialized nursing, pharmacy, dentistry)? Have you ever considered information services, specifically those centering on both the differences between your educational experience and retrieving and appraising scientific evidence. that of today’s professional students? How effective Information Retrieval & Appraisal Services in Medicine were educational strategies then compared to those employed today? In light of the extraordinary growth of the scientific literature, it is said that perhaps no industry is in greater The “Evidence Base” need of specialized information services than medicine. In all industries, especially medicine, the growing level of According to estimates, approximately 2.5 million experimentation and the pervasive expectation for an scientific journal manuscripts were published in 2009 in “evidence base” is very well established. Municipalities more than 29,000 journals.1 Between 1994 and 2001, and not-for-profit organizations, for instance, search for approximately 400,000 medical manuscripts were evidence-based interventions that address problems of published per year (on average),2 making medicine the homelessness, food insecurity, or public health. -
A Meta-Review of Transparency and Reproducibility-Related Reporting Practices in Published Meta- Analyses on Clinical Psychological Interventions (2000-2020)
A meta-review of transparency and reproducibility-related reporting practices in published meta- analyses on clinical psychological interventions (2000-2020). Rubén López-Nicolás1, José Antonio López-López1, María Rubio-Aparicio2 & Julio Sánchez- Meca1 1 Universidad de Murcia (Spain) 2 Universidad de Alicante (Spain) Author note: This paper has been published at Behavior Research Methods. The published version is available at: https://doi.org/10.3758/s13428-021-01644-z. All materials, data, and analysis script coded have been made publicly available on the Open Science Framework: https://osf.io/xg97b/. Correspondence should be addressed to Rubén López-Nicolás, Facultad de Psicología, Campus de Espinardo, Universidad de Murcia, edificio nº 31, 30100 Murcia, España. E-mail: [email protected] 1 Abstract Meta-analysis is a powerful and important tool to synthesize the literature about a research topic. Like other kinds of research, meta-analyses must be reproducible to be compliant with the principles of the scientific method. Furthermore, reproducible meta-analyses can be easily updated with new data and reanalysed applying new and more refined analysis techniques. We attempted to empirically assess the prevalence of transparency and reproducibility-related reporting practices in published meta-analyses from clinical psychology by examining a random sample of 100 meta-analyses. Our purpose was to identify the key points that could be improved with the aim to provide some recommendations to carry out reproducible meta-analyses. We conducted a meta-review of meta-analyses of psychological interventions published between 2000 and 2020. We searched PubMed, PsycInfo and Web of Science databases. A structured coding form to assess transparency indicators was created based on previous studies and existing meta-analysis guidelines. -
Evidence Based Policymaking’ in a Decentred State Abstract
Paul Cairney, Professor of Politics and Public Policy, University of Stirling, UK [email protected] Paper accepted for publication in Public Policy and Administration 21.8.19 Special Issue (Mark Bevir) The Decentred State The myth of ‘evidence based policymaking’ in a decentred state Abstract. I describe a policy theory story in which a decentred state results from choice and necessity. Governments often choose not to centralise policymaking but they would not succeed if they tried. Many policy scholars take this story for granted, but it is often ignored in other academic disciplines and wider political debate. Instead, commentators call for more centralisation to deliver more accountable, ‘rational’, and ‘evidence based’ policymaking. Such contradictory arguments, about the feasibility and value of government centralisation, raise an ever-present dilemma for governments to accept or challenge decentring. They also accentuate a modern dilemma about how to seek ‘evidence-based policymaking’ in a decentred state. I identify three ideal-type ways in which governments can address both dilemmas consistently. I then identify their ad hoc use by UK and Scottish governments. Although each government has a reputation for more or less centralist approaches, both face similar dilemmas and address them in similar ways. Their choices reflect their need to appear to be in control while dealing with the fact that they are not. Introduction: policy theory and the decentred state I use policy theory to tell a story about the decentred state. Decentred policymaking may result from choice, when a political system contains a division of powers or a central government chooses to engage in cooperation with many other bodies rather than assert central control. -
John P.A. Ioannidis | Stanford Medicine Profiles
06/01/2021 John P.A. Ioannidis | Stanford Medicine Profiles CAP Profiles John P.A. Ioannidis PROFESSOR OF MEDICINE (STANFORD PREVENTION RESEARCH), OF EPIDEMIOLOGY AND POPULATION HEALTH AND BY COURTESY, OF STATISTICS AND OF BIOMEDICAL DATA SCIENCE Medicine - Stanford Prevention Research Center PRINT PROFILE EMAIL PROFILE Profile Tabs Menu Bio C.F. Rehnborg Chair in Disease Prevention, Professor of Medicine, of Epidemiology and Population Health, and (by courtesy) of Biomedical Data Science, and of Statistics; co-Director, Meta-Research Innovation Center at Stanford (METRICS). Born in New York City in 1965 and raised in Athens, Greece. Valedictorian (1984) at Athens College; National Award of the Greek Mathematical Society (1984); MD (top rank of medical school class) from the National University of Athens in 1990; also received DSc in biopathology from the same institution. Trained at Harvard and Tus (internal medicine and infectious diseases), then held positions at NIH, Johns Hopkins and Tus. Chaired the Department of Hygiene and Epidemiology, University of Ioannina Medical School in 1999-2010 while also holding adjunct professor positions at Harvard, Tus, and Imperial College. Senior Advisor on Knowledge Integration at NCI/NIH (2012-6). Served as President, Society for Research Synthesis Methodology, and editorial board member of many leading journals (including PLoS Medicine, Lancet, Annals of Internal Medicine, JNCI among others) and as Editor-in-Chief of the European Journal of Clinical Investigation (2010-2019). Delivered ~600 invited and honorary lectures. Recipient of many awards (e.g. European Award for Excellence in Clinical Science [2007], Medal for Distinguished Service, Teachers College, Columbia University [2015], Chanchlani Global Health Award [2017], Epiphany Science Courage Award [2018], Einstein fellow [2018]). -
Mass Production of Systematic Reviews and Meta-Analyses: an Exercise in Mega-Silliness?
Commentary Mass Production of Systematic Reviews and Meta-analyses: An Exercise in Mega-silliness? MATTHEW J. PAGE∗,† and DAVID MOHER‡,§ ∗School of Public Health and Preventive Medicine, Monash University; †School of Social and Community Medicine, University of Bristol; ‡Centre for Practice Changing Research, Ottawa Hospital Research Institute; §School of Epidemiology, Public Health and Preventive Medicine, Faculty of Medicine, University of Ottawa n 1978, the distinguished professor of psychology Hans Eysenck delivered a scathing critique of what was then a new I method, that of meta-analysis, which he described as “an exer- cise in mega-silliness.” A provocative article by John Ioannidis in this issue of the journal1 suggests that “mega-silliness” may be an appro- priate characterization of what the meta-analysis literature has become. With surveys of the PubMed database and other empirical evaluations, Ioannidis paints a disturbing picture of the current state of affairs, where researchers are producing, in epidemic proportions, systematic reviews and meta-analyses that are redundant, misleading, or serving vested interests. Ioannidis presents an astounding case of 21 different meta-analyses of statins for atrial fibrillation in cardiac surgery published within a period of 7 years, with some of these having practically identical results.1 Moreover, his findings are in line with our recent cross-sectional study of systematic reviews of biomedical research.2 We identified 682 systematic reviews indexed in MEDLINE in a single month (February 2014), which is equivalent to 22 reviews published per day. The majority of reviews did not consider study risk of biases or other reporting biases when drawing conclusions. -
1 Lessons from the Evidence on Evidence-Based Policy Richard D. French Introduction What Can We Learn from the Evidence on Evide
Lessons from the Evidence on Evidence-based Policy Richard D. French Introduction What can we learn from the evidence on evidence-based policy (EBP)? We cannot do a randomized controlled test, as dear to the hearts of many proponents of EBP as that method may be. Much of the “evidence” in question will not meet the standards of rigour demanded in the central doctrine of EBP, but we are nevertheless interested in knowing, after a number of years as an idea in good currency, what we have gathered from the pursuit of EBP. In one of the most important surveys of research use, Sandra Nutley, Isabel Walter and Huw Davies (Nutley et al 2007, 271) note that: As anyone working in the field of research use knows, a central irony is the only limited extent to which evidence advocates can themselves draw on a robust evidence base to support their convictions that greater evidence use will ultimately be beneficial to public services. Our conclusions…are that we are unlikely any time soon to see such comprehensive evidence neatly linking research, research use, and research impacts, and that we should instead be more modest about what we can attain through studies that look for these. If then, we want to pursue our interest in the experience of EBP, we need to be open- minded about the sources we use. A search for “evidence-based policy” on the PAIS database produced 132 references in English. These references, combined with the author’s personal collection developed over the past several years, plus manual searches of the bibliographies of the books, book chapters and articles from these two original sources, produced around 400 works on EBP. -
“A Formidable Share of the Research We Pay for Is Simply Wrong.” by JON KÅRE TIME, Appeared in MORGENBLADET, No
“A formidable share of the research we pay for is simply wrong.” By JON KÅRE TIME, appeared in MORGENBLADET, No. 22/8–14 June 2018 Translated from the Norwegian by Heidi Sommerstad Ødegård, AMESTO/Semantix Translations Norway AS, Torture of data, perverse reward systems, declining morals and false findings: Science is in crisis argues statistician Andrea Saltelli. “There’s been a lot of data torturing with this cool dataset,” wrote Cornell University food scientist Brian Wansink in a message to a colleague. Wansink was famous, and his research was popular. It showed, among other things, how to lose weight without much effort. All anyone needed to do was make small changes to their habits and environment. We eat less if we put the cereal boxes in the cabinet instead of having it out on the counter. But after an in-depth investigation by Buzzfeed earlier this year, Wansink has fallen from grace as a social science star to a textbook example of what respectable scientists do not do. “Data torturing” is also referred to as “p-hacking” – the slicing and dicing of a dataset until you find a statistical context that is strong and exciting enough to publish. As Wansink himself formulated it in one of the uncovered emails, you can “tweak” the dataset to find what you want. “Think about all the different ways you can cut the data,” he wrote to a new grad student about to join his lab. It’s a crisis! “Is science in crisis? Well, it was perhaps debatable a few years ago, but now?” Andrea Saltelli seems almost ready to throw up his hands in despair at the question.