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  1. Measuring effectiveness.Jacob Stegenga - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:62-71.
    Measuring the effectiveness of medical interventions faces three epistemological challenges: the choice of good measuring instruments, the use of appropriate analytic measures, and the use of a reliable method of extrapolating measures from an experimental context to a more general context. In practice each of these challenges contributes to overestimating the effectiveness of medical interventions. These challenges suggest the need for corrective normative principles. The instruments employed in clinical research should measure patient-relevant and disease-specific parameters, and should not be sensitive (...)
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  • Rationality and the generalization of randomized controlled trial evidence.Jonathan Fuller - 2013 - Journal of Evaluation in Clinical Practice 19 (4):644-647.
    Over the past several decades, we devoted much energy to generating, reviewing and summarizing evidence. We have given far less attention to the issue of how to thoughtfully apply the evidence once we have it. That’s fine if all we care about is that our clinical decisions are evidence-based, but not so good if we also want them to be well-reasoned. Let us not forget that evidence based medicine (EBM) grew out of an interest in making medicine ‘rational’, with the (...)
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  • Aspects of Scientific Explanation and Other Essays in the Philosophy of Science.Carl Gustav Hempel - 1965 - New York: The Free Press.
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  • (1 other version)What evidence in evidence-based medicine?John Worrall - 2002 - Proceedings of the Philosophy of Science Association 2002 (3):S316-S330.
    Evidence-Based Medicine is a relatively new movement that seeks to put clinical med- icine on a firmer scientific footing. I take it as uncontroversial that medical practice should be based on best evidence-the interesting questions concern the details. This paper tries to move towards a coherent and unified account of best evidence in medicine, by exploring in particular the EBM position on RCTs (randomized controlled trials).
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  • Inductive risk and values in science.Heather Douglas - 2000 - Philosophy of Science 67 (4):559-579.
    Although epistemic values have become widely accepted as part of scientific reasoning, non-epistemic values have been largely relegated to the "external" parts of science (the selection of hypotheses, restrictions on methodologies, and the use of scientific technologies). I argue that because of inductive risk, or the risk of error, non-epistemic values are required in science wherever non-epistemic consequences of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic consequences of error can and should be considered (...)
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  • Absence of evidence and evidence of absence: evidential transitivity in connection with fossils, fishing, fine-tuning, and firing squads.Elliott Sober - 2009 - Philosophical Studies 143 (1):63-90.
    “Absence of evidence isn’t evidence of absence” is a slogan that is popular among scientists and nonscientists alike. This article assesses its truth by using a probabilistic tool, the Law of Likelihood. Qualitative questions (“Is E evidence about H ?”) and quantitative questions (“How much evidence does E provide about H ?”) are both considered. The article discusses the example of fossil intermediates. If finding a fossil that is phenotypically intermediate between two extant species provides evidence that those species have (...)
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  • Rhetoric and argumentation: how clinical practice guidelines think.Jonathan Fuller - 2013 - Journal of Evaluation in Clinical Practice 19 (3):433-441.
    Introduction: Clinical practice guidelines (CPGs) are an important source of justification for clinical decisions in modern evidence-based practice. Yet, we have given little attention to how they argue their evidence. In particular, how do CPGs argue for treatment with long-term medications that are increasingly prescribed to older patients? Approach and rationale: I selected six disease-specific guidelines recommending treatment with five of the medication classes most commonly prescribed for seniors in Ontario, Canada. I considered the stated aims of these CPGs and (...)
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  • Across the boundaries: extrapolation in biology and social science.Daniel Steel (ed.) - 2007 - New York: Oxford University Press.
    Inferences like these are known as extrapolations.
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  • The Risk GP Model: The standard model of prediction in medicine.Jonathan Fuller & Luis J. Flores - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:49-61.
    With the ascent of modern epidemiology in the Twentieth Century came a new standard model of prediction in public health and clinical medicine. In this article, we describe the structure of the model. The standard model uses epidemiological measures-most commonly, risk measures-to predict outcomes (prognosis) and effect sizes (treatment) in a patient population that can then be transformed into probabilities for individual patients. In the first step, a risk measure in a study population is generalized or extrapolated to a target (...)
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  • What are randomised controlled trials good for?Nancy Cartwright - 2009 - Philosophical Studies 147 (1):59 - 70.
    Randomized controlled trials (RCTs) are widely taken as the gold standard for establishing causal conclusions. Ideally conducted they ensure that the treatment ‘causes’ the outcome—in the experiment. But where else? This is the venerable question of external validity. I point out that the question comes in two importantly different forms: Is the specific causal conclusion warranted by the experiment true in a target situation? What will be the result of implementing the treatment there? This paper explains how the probabilistic theory (...)
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  • Rules for reasoning from knowledge and lack of knowledge.Douglas Walton - 2006 - Philosophia 34 (3):355-376.
    In this paper, the traditional view that argumentum ad ignorantiam is a logical fallacy is challenged, and lessons are drawn on how to model inferences drawn from knowledge in combination with ones drawn from lack of knowledge. Five defeasible rules for evaluating knowledge-based arguments that apply to inferences drawn under conditions of lack of knowledge are formulated. They are the veridicality rule, the consistency of knowledge rule, the closure of knowledge rule, the rule of refutation and the rule for argument (...)
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  • Philosophy of epidemiology.Alex Broadbent - 2016 - In Miriam Solomon, Jeremy R. Simon & Harold Kincaid (eds.), The Routledge Companion to Philosophy of Medicine. New York, NY: Routledge.
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  • (1 other version)What Evidence in Evidence‐Based Medicine?John Worrall - 2002 - Philosophy of Science 69 (S3):S316-S330.
    Evidence-Based Medicine is a relatively new movement that seeks to put clinical medicine on a firmer scientific footing. I take it as uncontroversial that medical practice should be based on best evidence—the interesting questions concern the details. This paper tries to move towards a coherent and unified account of best evidence in medicine, by exploring in particular the EBM position on RCTs.
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  • Problems with using mechanisms to solve the problem of extrapolation.Jeremy Howick, Paul Glasziou & Jeffrey K. Aronson - 2013 - Theoretical Medicine and Bioethics 34 (4):275-291.
    Proponents of evidence-based medicine and some philosophers of science seem to agree that knowledge of mechanisms can help solve the problem of applying results of controlled studies to target populations (‘the problem of extrapolation’). We describe the problem of extrapolation, characterize mechanisms, and outline how mechanistic knowledge might be used to solve the problem. Our main thesis is that there are four often overlooked problems with using mechanistic knowledge to solve the problem of extrapolation. First, our understanding of mechanisms is (...)
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  • Presidential Address: Will This Policy Work for You? Predicting Effectiveness Better: How Philosophy Helps.Nancy Cartwright - 2012 - Philosophy of Science 79 (5):973-989.
    There is a takeover movement fast gaining influence in development economics, a movement that demands that predictions about development outcomes be based on randomized controlled trials. The problem it takes up—of using evidence of efficacy from good studies to predict whether a policy will be effective if we implement it—is a general one, and affects us all. My discussion is the result of a long struggle to develop the right concepts to deal with the problem of warranting effectiveness predictions. Whether (...)
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  • A philosopher's view of the long road from RCTs to effectiveness.Nancy Cartwright - 2011 - The Lancet 377 (9775):1400-1401.
    For evidence-based practice and policy, randomised controlled trials (RCTs) are the current gold standard. But exactly why? We know that RCTs do not, without a series of strong assumptions, warrant predictions about what happens in practice. But just what are these assumptions? I maintain that, from a philosophical stance, answers to both questions are obscured because we don't attend to what causal claims say. Causal claims entering evidence-based medicine at different points say different things and, I would suggest, failure to (...)
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  • How to generalize efficacy results of randomized trials: recommendations based on a systematic review of possible approaches.Piet N. Post, Hans Beer & Gordon H. Guyatt - 2013 - Journal of Evaluation in Clinical Practice 19 (4):638-643.
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