The Twentieth Century has seen a dramatic rise in the use of probability and statistics in almost all fields of research. This has stimulated many new philosophical ideas on probability. _Philosophical Theories of Probability_ is the first book to present a clear, comprehensive and systematic account of these various theories and to explain how they relate to one another. Gillies also offers a distinctive version of the propensity theory of probability, and the intersubjective interpretation, which develops the subjective theory.

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 (...) of causality implies that RCTs can establish causal conclusions and thereby provides an account of what exactly that causal conclusion is. Clarifying the exact form of the conclusion shows just what is necessary for it to hold in a new setting and also how much more is needed to see what the actual outcome would be there were the treatment implemented. (shrink)

An astonishing volume and diversity of evidence is available for many hypotheses in the biomedical and social sciences. Some of this evidence—usually from randomized controlled trials (RCTs)—is amalgamated by meta-analysis. Despite the ongoing debate regarding whether or not RCTs are the ‘gold-standard’ of evidence, it is usually meta-analysis which is considered the best source of evidence: meta-analysis is thought by many to be the platinum standard of evidence. However, I argue that meta-analysis falls far short of that standard. Different meta-analyses (...) of the same evidence can reach contradictory conclusions. Meta-analysis fails to provide objective grounds for intersubjective assessments of hypotheses because numerous decisions must be made when performing a meta-analysis which allow wide latitude for subjective idiosyncrasies to influence its outcome. I end by suggesting that an older tradition of evidence in medicine—the plurality of reasoning strategies appealed to by the epidemiologist Sir Bradford Hill—is a superior strategy for assessing a large volume and diversity of evidence. (shrink)

Philosophers of science have insisted that evidence of underlying mechanisms is required to support claims about the effects of medical interventions. Yet evidence about mechanisms does not feature on dominant evidence-based medicine “hierarchies.” After arguing that only inferences from mechanisms (“mechanistic reasoning”)—not mechanisms themselves—count as evidence, I argue for a middle ground. Mechanistic reasoning is not required to establish causation when we have high-quality controlled studies; moreover, mechanistic reasoning is more problematic than has been assumed. Yet where the problems can (...) be overcome, mechanistic reasoning can and should be used as evidence. (shrink)

To explain the phenomena in the world of our experience, to answer the question “why?” rather than only the question “what?”, is one of the foremost objectives of all rational inquiry; and especially, scientific research in its various branches strives to go beyond a mere description of its subject matter by providing an explanation of the phenomena it investigates. While there is rather general agreement about this chief objective of science, there exists considerable difference of opinion as to the function (...) and the essential characteristics of scientific explanation. In the present essay, an attempt will be made to shed some light on these issues by means of an elementary survey of the basic pattern of scientific explanation and a subsequent more rigorous analysis of the concept of law and of the logical structure of explanatory arguments. (shrink)

Semmelweis’s investigations of puerperal fever are some of the most interesting in the history of medicine. This paper considers Hempel’s analysis of the Semmelweis case. It argues that this analysis is inadequate and needs to be supplemented by some Kuhnian ideas. Kuhn’s notion of paradigm needs to be modified to apply to medicine in order to take account of the classification schemes involved in medical theorising. However with a suitable modification it provides an explanation of Semmelweis’s failure which is argued (...) to be superior to some of the external reasons often given. Despite this success in applying Kuhn’s ideas to medicine, it is argued that these ideas must be further modified to take account of the fact that medicine is not a natural science but primarily a practice designed to prevent and cure diseases. (shrink)

Semmelweis’s investigations of puerperal fever are some of the most interesting in the history of medicine. This paper considers Hempel’s analysis of the Semmelweis case. It argues that this analysis is inadequate and needs to be supplemented by some Kuhnian ideas. Kuhn’s notion of paradigm needs to be modified to apply to medicine in order to take account of the classification schemes involved in medical theorising. However with a suitable modification it provides an explanation of Semmelweis’s failure which is argued (...) to be superior to some of the external reasons often given. Despite this success in applying Kuhn’s ideas to medicine, it is argued that these ideas must be further modified to take account of the fact that medicine is not a natural science but primarily a practice designed to prevent and cure diseases. (shrink)

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 (...) the techniques employed towards those aims. Finally, I reconstructed and logically analysed the arguments supporting recommendations for pharmacotherapy. Analysis: The primary function of CPGs is rhetorical, or persuasive, and their means of persuasion include both a display of their credibility and their argumentation. Arguments supporting pharmacotherapy recommendations for the target population follow a common inductive pattern: statistical generalization from randomized controlled trial (RCT) and meta-analysis evidence. Two of the CPGs also argue their treatment recommendations for older patients in this style, while three fail to justify pharmacotherapy specifically for the older population. Discussion: The arguments analysed lack the auxiliary assumptions that would warrant making a generalization about the clinical effectiveness of medications for the older population. Guidelines reason using simple induction, while ignoring important inferential gaps. Future guidelines should aspire to be well-reasoned rather than simply evidence-based; argue from a plurality of evidence; be wary of hasty inductions; appropriately limit the scope of their recommendations; and avoid making law-like, prescriptive generalizations. (shrink)

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 (...) idea that rational clinical evaluations should be evidence-based. I agree with the uncontroversial statement that the best decision is supported, at least in part, by the best available evidence. Rationality, however, is constituted by reasoning, not evidence. Complete arguments are necessary for rational evaluations, arguments that begin with general evidence and end in a conclusion about a particular patient. In order to traverse these inferential gaps, medicine must address the issue of how to establish, as an intermediate premise, what the evidence has to say about the efficacy of an intervention for particular patients in a particular practice setting. (shrink)

Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in (...) explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM. (shrink)

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 (...) I have it right or not, these are questions of vast social importance that philosophers of science can, and should, help answer. (shrink)

Among the various meanings in which the word ‘probability’ is used in everyday language, in the discussion of scientists, and in the theories of probability, there are especially two which must be clearly distinguished. We shall use for them the terms ‘probability1’ and ‘probability2'. Probability1 is a logical concept, a certain logical relation between two sentences ; it is the same as the concept of degree of confirmation. I shall write briefly “c” for “degree of confirmation,” and “c” for “the (...) degree of confirmation of the hypothesis h on the evidence e“; the evidence is usually a report on the results of our observations. On the other hand, probability2 is an empirical concept; it is the relative frequency in the long run of one property with respect to another. The controversy between the so-called logical conception of probability, as represented e.g. by Keynes, and Jeffreys, and others, and the frequency conception, maintained e.g. by v. Mises and Reichenbach, seems to me futile. These two theories deal with two different probability concepts which are both of great importance for science. Therefore, the theories are not incompatible, but rather supplement each other. (shrink)

The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

Even though the evidence‐based medicine movement (EBM) labels mechanisms a low quality form of evidence, consideration of the mechanisms on which medicine relies, and the distinct roles that mechanisms might play in clinical practice, offers a number of insights into EBM itself. In this paper, I examine the connections between EBM and mechanisms from several angles. I diagnose what went wrong in two examples where mechanistic reasoning failed to generate accurate predictions for how a dysfunctional mechanism would respond to intervention. (...) I then use these examples to explain why we should expect this kind of mechanistic reasoning to fail in systematic ways, by situating these failures in terms of evolved complexity of the causal system(s) in question. I argue that there is still a different role in which mechanisms continue to figure as evidence in EBM: namely, in guiding the application of population‐level recommendations to individual patients. Thus, even though the evidence‐based movement rejects one role in which mechanistic reasoning serves as evidence, there are other evidentiary roles for mechanistic reasoning. This renders plausible the claims of some critics of evidencebased medicine who point to the ineliminable role of clinical experience. Clearly specifying the ways in which mechanisms and mechanistic reasoning can be involved in clinical practice frames the discussion about EBM and clinical experience in more fruitful terms. (shrink)

The philosophy of evidence-based medicine -- What is EBM? -- What is good evidence for a clinical decision? -- Ruling out plausible rival hypotheses and confounding factors : a method -- Resolving the paradox of effectiveness : when do observational studies offer the same degree of evidential support as randomized trials? -- Questioning double blinding as a universal methodological virtue of clinical trials : resolving the Philip's paradox -- Placebo controls : problematic and misleading baseline measures of effectiveness -- Questioning (...) the methodological superiority of "placebo" over "active" controlled trials -- Examining the paradox that traditional roles for mechanistic reasoning and expert -- Judgment have been up-ended by EBM -- A qualified defence of the EBM stance on mechanistic reasoning -- Knowledge that versus knowledge how : situating the EBM position on expert clinical judgment -- Moving EBM forward. (shrink)

Inferences like these are known as extrapolations.

This is an introductory 2001 textbook on probability and induction written by one of the world's foremost philosophers of science. The book has been designed to offer maximal accessibility to the widest range of students and assumes no formal training in elementary symbolic logic. It offers a comprehensive course covering all basic definitions of induction and probability, and considers such topics as decision theory, Bayesianism, frequency ideas, and the philosophical problem of induction. The key features of this book are a (...) lively and vigorous prose style; lucid and systematic organization and presentation of ideas; many practical applications; a rich supply of exercises drawing on examples from such fields as psychology, ecology, economics, bioethics, engineering, and political science; numerous brief historical accounts of how fundamental ideas of probability and induction developed; and a full bibliography of further reading. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

The proposed practice of "evidence-based medicine," which calls for careful clinical judgment in evaluating the "best available evidence," should be differentiated from the special collection of data regarded as suitable evidence. Although the proposed practice does not seem new, the new collection of "best available" information has major constraints for the care of individual patients. Derived almost exclusively from randomized trials and meta-analyses, the data do not include many types of treatments or patients seen in clinical practice; and the results (...) show comparative efficacy of treatment for an "average" randomized patient, not for pertinent subgroups formed by such cogent clinical features as severity of symptoms, illness, co-morbidity, and other clinical nuances. The intention-to-treat analyses do not reflect important post-randomization events leading to altered treatment; and the results seldom provide suitable background data when therapy is given prophylactically rather than remedially, or when therapeutic advantages are equivocal. Randomized trial information is also seldom available for issues in etiology, diagnosis, and prognosis, and for clinical decisions that depend on pathophysiologic changes, psychosocial factors and support, personal preferences of patients, and strategies for giving comfort and reassurance. The laudable goal of making clinical decisions based on evidence can be impaired by the restricted quality and scope of what is collected as "best available evidence." The authoritative aura given to the collection, however, may lead to major abuses that produce inappropriate guidelines or doctrinaire dogmas for clinical practice. (shrink)

It is often said that clinical research and the practice of medicine are fraught with uncertainties. But what do we mean by uncertainty? Where does uncertainty come from? How do we measure uncertainty? Is there a single theory of uncertainty that applies across all scientific domains, including the science and practice of medicine? To answer these questions, we first review the existing theories of uncertainties. We then attempt to bring the enormous literature to bear from other disciplines to address the (...) issue of uncertainty in clinical research and medical practice. Our main and overarching goal is to review and classify uncertainties in clinical medicine. (shrink)