Archive for June, 2013

Choosing a narrative in isolation: Fisher, Popper and p-values (Part II)

June 27, 2013

In the second part of this post we will see how one can reject an incomplete (from Popper’s perspective) scientific narrative using significance tests without making an appeal to the frequency interpretation of probability. Actually there are at least two paths, both of which can be seen as numerical approximations to a Bayesian selection procedure. (more…)

Choosing a narrative in isolation: Fisher, Popper and p-values (Part I)

June 26, 2013

Most applied work in scientific exploration also involves a choice among narratives: an experiment is designed on the basis of a premise being true and when the experiment is performed, data are collected and a paper is written. The latter (among other things) puts the data in the litmus of a statistical significance test to yield a p-value that the investigators use to reject the original hypothesis (if the p-value is small) or not reject it (if the p-value is large). Unfortunately large p-values usually have the undesired consequence that the research paper and the experiment are rejected from the scientific record, i.e. they are never accepted for publication: (more…)

How to choose among alternative narratives

June 25, 2013

The arithmetic of choosing among alternative narratives in the clinic and elsewhere, can be made rigorous by selecting a numerical scale for representing the extremes of falseness/impossibility all the way truthfulness/certainty. If the scale is selected as a probability one ranging from 0 to 1 and certain rules for the manipulation of probabilities as mathematical objects are employed, then one arrives at a formal inferential system. This system which allows for a logically consistent reasoning in the face of uncertainty is known as Bayesian probability theory and its modern development can be found in the texts by Keynes, Cox and Jaynes. (more…)

Medical diagnosis is a choice among narratives

June 22, 2013

The availability of narratives i.e. experience-based, organized stories about the world,  is an important tool allowing us to navigate our everyday tasks. During clinical work in particular, selecting one among many narratives is a very common task and one fraught with risk for physicians and patients alike. Consider the following, extremely common, scenario in my practice: a patient walks in a physician’s office with an elevated reading of his or hers Blood Pressure (BP) asking for an evaluation. The physician’s task at this point is two-fold:

  • first, to confirm the presence of elevated BP (giving the patient the diagnosis of a hypertensive condition)
  • second, to decide whether the patient has one of the many known disease states causing high BP (this is known as Secondary Hypertension)  or finding no known cause, give the patient the diagnosis of Essential/Idiopathic (“don’t know what is going on”) Hypertension


Data as stories, models as narratives

June 21, 2013

Ever since the first humans gathered around their first fires (or even before that!) we absolutely love to listen (and tell) stories, parables, narratives about real or fictional events. Notwithstanding the important roles these activities played in facilitating social organization, there are reasons to pay particular attention to modes of story telling if we are to understand the way science works. By that I do not mean the particular mechanics of a given scientific theory (e.g. how atoms are structured, whether a group of medications works in a disease or even if stimulus packages or austerity works), but rather how theories come about, how they flourish and then abandoned for something else. The sociology of the scientific process has been described  by Thomas Kuhn in his Structure of Scientific Revolutions, but drawing an analogy with more familiar territory may be of some value.