When one comes up on two diametrically opposing views, it turns
into a learning experience of how both sides cannot proverbially see the forest
of the trees? When one side claims and tugs and pushes its viewpoint to the
point of abstraction and the other emulates with equal passion somewhere in
that monologue from either side lies the seed for a dialog, a seed, that
neither one sees. Don’t you think?
Two households both alike in dignity, are drawn to ancient
grudge to bring proof of their supreme excellence. The Epidemiological house derides
the Randomized Controlled Trial house as too focused and limited in scope due
to its optimized conditions, which does not meet the requirements of the large
populations. And that is true to a large extent, even Thomas Bayes, he of the
English statistician, philosopher and Presbyterian minister fame would agree
that using random samples can only have so much strength and integrity to export
validity of a meager sampled experiment to an entire population.
Meanwhile the reductionist household of empiricists are also employing the same war chest. Both sides want to win the argument: Population statistics and results equate at the individual level and small samples of the population equate to the whole population is the new creed of this crude thought. Both sides employing similar tools are being drawn to a similar conclusion: The “missionary” work of the empiricists however would look
at it the other way and say, “we, of the
reductionist point of view, from deciphering the needs of a few can determine
what ails the whole society. Our carefully crafted experiments see the forest
as it represents itself !” They however
momentarily forget those new saplings and an occasional oak on either side of
their 95% curved landscape.
So who is right? Maybe neither!
The Epidemiologists now have a new war chest. The Biggish Data
that they are fond of using for proof of their methodology seems to satisfy
their needs. They no longer find the need to get their hands dirty. They merely
need to ascertain the weight of the compiled digits that someone has keyed into
the servers. Data defines
reality for all! Or does it? Is it the data, its selection or its manipulation
that defines the concocted reality? One must also remember the Bird Flu A(H1N1) rallied by the World Health Organization as an pandemic in 2009, wasn't! It is a stark reminder of the strong carry-trade
of emotional currency, when projections based on math overwhelm logic and
reason! Not only was the logic denuded of reliable data but the fear-mongering projections
thus mathematically reasoned were accentuated only by the comparisons between the Bird Flu of
2009 to the Influenza of 1918.
From the ePluribus Unum we have arrived at ex multis! John
Snow, he of Cholera as a waterborne disease rather than air-borne fame, would
be resigned to depression today. After all, epidemiology certainly has a part
to play in protecting the population from potential risk, but utilizing the
large umbrella of public safety could these experts venture into the habitat of
the empiricists without so much as a nod to the causality, except by dint of
thought or bias? In other words can the protective umbrella of the
epidemiologist wrongfully detract from reality by force-seeking the causality
without hurtling through the rigors of the empiricist’s evidence, which are similar
in scope and therefore be blinded to project false causality to the whole or a
select portion of the citizenry? Ah therein lie the seeds of discord!
Epidemiology studies are a boon for societies as a whole, if
they are done correctly to find causal factors of potential vectors of the flame that incite wide-spread
epidemics. But using limited data arrived
at through statistical torture and casting it as a wide net of causality can
prove a detriment to science itself. Today the rigors go so far as to admit and
deny the causal factors of an affliction in the same breath. There are a lot of
“mays” and “mights” thrown around for full disclosure and future immunity.
The purity of science is in the rigor and not in the
shortcuts that one seeks today to publish, gain recognition, make a name for
oneself, get a promotion and seek further advancement among one’s peers. That
desire of self-aggrandizement, based on the mishmash of the scientific conversations
in print seems diametrically at odds with good science. John Iannodis, MD in his
article, “Why Most Published Research
Findings Are False,” found that more than 50% of the experimental studies
were unverifiable! With the 15-minute fame over, the focus of the scientist-statistician
moves on towards new mining.
In the world of data-mining from large data-warehouses where
any selected digit is a means to an end and reliance upon the statistical
methodology so employed a means to a better future, science suffers from such
inaccuracies. Both sides are embroiled in the latest rendition of such thought that
would compile the argument into a tightly bound Confidence Interval and then
determine the 95% probability making all other nuances of differing thoughts, mere distractions.
There is an epidemic of false starts and forced understanding
in medical science today. It is time to unwind the clocks and rethink our
future otherwise this pleiotropic nature of “one size fits all” will indeed one
day end individualism, creativity and innovation. It is time for each side to think its own set of tools and merge the information for a unified theory of existence where real world problems are handled through real world thinking, not some sham-based probabilities!
http://m.ghspjournal.org/content/2/3/253.full
http://blogs.scientificamerican.com/the-curious-wavefunction/2013/05/20/cancer-genomics-and-technological-solutionism-a-time-to-be-wary/
