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!