Chance News 64
Quotations
We tolerate the pathologies of quantification — a dry, abstract, mechanical type of knowledge — because the results are so powerful. Numbering things allows tests, comparisons, experiments. Numbers make problems less resonant emotionally but more tractable intellectually. In science, in business and in the more reasonable sectors of government, numbers have won fair and square.
--Gary Wolf
Writing in The data-driven life, New York Times, 26 April 2010
Submitted by Bill Peterson
Forsooth
Fixing the census
The following article was suggested by Laura Chihara suggested on the Isolated Statisticians list:
The census will be wrong. We could fix it.
by Jordan Ellenberg, Washington Post, 1 May 2010
Odds are, it’s wrong--Part II
An entry in Chance News 63 presented a Science News article by Tom Siegfried. The article, which focuses on statistics used in the medical field, may be found here and is worth some elaboration; be sure to read the the comments reacting to what Siegfried writes. There you will find mention of circumcision, condoms, defense of statistics in medicine, praise for the author, condemnation of the author--and somehow, reference to Scott Reuben, who faked data for Pfizer and Merck (see Serious medical fraud in Chance News 45).
Siegfried’s main contention is that despite its prevalence in the medical sphere (and dominance elsewhere as well), Fisher’s p-value approach is inadequate and misleading at best. Because of this “p-value mania,” Siegfried quotes two researchers who claim “that in modern [medical] research, false findings may be the majority or even the vast majority of published research claims,” and “There are more false claims made in the medical literature than anybody appreciates,” respectively.
Criticism of p-value is hardly new. Put “criticism of p-value” into a browser and you will get 4,520,000 hits, many of which are more informative than Siegfried’s article. Try The P-value, devalued from the International Journal of Epidemiology as an example.
Discussion
1. To see why critics of p-value say it is the wrong-way round, consider Prob ( brown eyes | Costa Rican) and Prob (Costa Rican | brown eyes). Compare with Prob (data | Null Hypothesis is true) and Prob (Null Hypothesis is true | data). For an interesting illustration of the difference between these conditional probabilities regarding the O.J. Simpson murder case see Steven Strogatz’s NYT article (25 April 2010).
2. Critics of p-value say that the above #1 is not strong enough of a criticism because p-value deals not with “data” that actually occurred but with “data at least this extreme.” Why is this a potent criticism?
3. Siegfried rightfully refers to “randomized, controlled clinical trials that test drugs for their ability to cure or their power to harm” as the “gold standard” for medical research. “Such trials assign patients at random to receive either the substance being tested or a placebo.” However, see Judson’s NYT article, Enhancing the Placebo (3 May 2010), which discusses how non-placebo a placebo can be. What does this do to clinical trials and the gold standard?
4. Siegfried suggests that Bayesian inference is preferable to the frequentist p-value approach of Fisher. If this is so, why is it that p-value approach is so dominant, long after Fisher himself died?
Submitted by Paul Alper