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 (...) to parameters that are only indirectly relevant. Effectiveness always should be measured and reported in absolute terms (using measures such as 'absolute risk reduction'), and only sometimes should effectiveness also be measured and reported in relative terms (using measures such as 'relative risk reduction')-employment of relative measures promotes an informal fallacy akin to the base-rate fallacy, which can be exploited to exaggerate claims of effectiveness. Finally, extrapolating from research settings to clinical settings should more rigorously take into account possible ways in which the intervention in question can fail to be effective in a target population. (shrink)

This paper develops axiomatic foundations for a probabilistic-interventionist theory of causal strength. Transferring methods from Bayesian confirmation theory, I proceed in three steps: I develop a framework for defining and comparing measures of causal strength; I argue that no single measure can satisfy all natural constraints; I prove two representation theorems for popular measures of causal strength: Pearl's causal effect measure and Eells' difference measure. In other words, I demonstrate these two measures can be derived from a set of plausible (...) adequacy conditions. The paper concludes by sketching future research avenues. (shrink)

La autora presenta algunas criticas generales al proyecto de reducir las leyes causales a probabilidades. Además, muestra que las leyes causales son imprescindibles para poder diferenciar las strategias efectivas de las que no lo son y da un criterio para considerar cuando podemos deducir causalidad a través de datos estadísticos.

In this important book, Ellery Eells explores and refines philosophical conceptions of probabilistic causality. In a probabilistic theory of causation, causes increase the probability of their effects rather than necessitate their effects in the ways traditional deterministic theories have specified. Philosophical interest in this subject arises from attempts to understand population sciences as well as indeterminism in physics. Taking into account issues involving spurious correlation, probabilistic causal interaction, disjunctive causal factors, and temporal ideas, Professor Eells advances the analysis of what (...) it is for one factor to be a positive causal factor for another. A salient feature of the book is a theory of token level probabilistic causation in which the evolution of the probability of a later event from an earlier event is central. This will be a book of crucial significance to philosophers of science and metaphysicians; it will also prove stimulating to many economists, psychologists, and physicists. (shrink)

In a randomized clinical trial (RCT), a group of patients, initially assembled through a mixture of deliberation (involving explicit inclusion and exclusion criteria) and serendipity (which patients happen to walk into which doctor’s clinic while the trial is in progress), are divided by some random process into an experimental group (members of which will receive the therapy under test) and a control group (members of which will receive some other treatment – perhaps placebo, perhaps the currently standard treatment for the (...) condition at issue). In a ‘double blind’ trial neither the patient nor the clinician knows to which of the groups a particular patient belongs. The results of double blind randomized controlled trials are almost universally regarded as providing the ‘gold standard’ for evidence in medicine. Fairly extreme claims to this effect can be found in the literature. For example the statistician Tukey wrote (1977, p. 679) “almost the only source of reliable evidence [in medicine] … is that obtained from … carefully conducted randomised trials”. And the clinician Victor Herbert claimed (1977, p. 690) “..the only source of reliable evidence rising to the level of proof about the usefulness of any new therapy is that obtained from wellplanned and carefully conducted randomized, and, where possible, coded (double blind) clinical trials. [Other] studies may point in a direction, but cannot be evidence as lawyers use the term evidence to mean something probative … [that is] tending to prove or actually proving”. Finally, the still very influential movement in favour of ‘Evidence Based Medicine’ (EBM) that began at McMaster University in the 1980s was initially often regarded as endorsing the claim that only RCTs provide real scientifically telling evidence. (shrink)