Dear Allstatters,
I am aware that this debate closed some time ago, and hope that you will not find this email to be too self-seeking. What follows was not included in the SUMMARY posted, yet I feel it addresses the question in an even-handed way, unlike most correspondence I have seen on the subject.
"In my short experience consulting with personnel ranging from Nurses to
Professors, I find that most are either in awe of 'simple' classical
statistics (unwilling to accept fundamental assumptions such as i.i.d.), or
often positively against such statistics.
I must say, I empathise with this view point (for example, we are all
related, to an extent with each other, be it by blood, location,
time........, and so a random sample is not likely to be i.i.d.) Successful
consultancy is achieved by a compromise between the medic and the
statistician, if both are honest over their fundamental assumptions. In this
sense, classical statistics DOES make use of prior knowledge, and this prior
knowledge comes into play mostly AFTER the study is done. Most people are
more comfortable with this as 'the scientific method', but it does bias
towards self-fulfilling prophecy. Here, however, just how much of an effect
prior knowledge has had remains rather intangible.
Bayesian statistics would, I feel, be a bridge too far for my customers.
While it allows one to express, quantitatively, the extent of the
involvement of prior knowledge, it is not seen to meet the ideal of the
scientific method, and, moreover, compounds the believed lack of adherence
to the fundamental statistical assumptions (e.g. i.i.d.) being made.
Classical statistics is what most know, and most often published. As
research must be published, and is most often undertaken principally with
that objective in mind, I feel that my customers might allow me to adopt
Bayesian Statistics for a more academic, statistical paper that I wished to
write, but are mostly after simple straightforward statistics that they feel
(going to the lowest common denominator) that their colleagues will
understand or wish to read.
I do not feel that even just Classical Statistics will move forward further
into the Medical Statistics in Practice arena until common ground is found
between Statistics and Medicine in terms of their fundamental assumptions.
And this needs/must be driven by the journals themselves. I am interested in
setting up a separate MEDICAL statistics email list to address these
concerns (which are more unique to Medical Statistics). What do you think ?"
I would only add the following philosophical wander:
Science is but art (at the level of the individual) that exists with boundaries agreed upon at the collective level, 'invented' by those chosen by the 'collective' as experts; statistics allows one to test out how individuals might match up to these collective models. Classical statistics has the problem that the method of chosing a model's boundaries is somewhat remote from every day reality; Bayesian statistics has the problem of the boundaries being set depending on the strength of experts existing boundaries (could Einstein have overcome Newton in this way ?).
Best Wishes,
Martin Holt
Medical Statistician
Southern Derbyshire Acute Hospitals Trust
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