July 2012
Intermediate to advanced
352 pages
9h 30m
English
book
Common Errors in Statistics (and How to Avoid Them), 4th Edition
by Phillip I. Good, James W. Hardin
Content preview from Common Errors in Statistics (and How to Avoid Them), 4th Edition
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ARE EXPERIMENTS REALLY NECESSARY?
In the case of rare diseases and other rare events, it is tempting to begin with the data in hand, that is, the records of individuals known to have the disease rather than to draw a random and expensive sample from the population at large. There is a right way and a wrong way to conduct such studies.
The wrong way is to reason backward from effect to cause. Suppose that the majority of victims of pancreatic cancer are coffee drinkers. Does this mean that coffee causes pancreatic cancer? Not if the majority of individuals in the population in which the cases occurred are coffee drinkers also.
To be sure, suppose we create a set of case controls, matching each individual in the pancreatic data base with an individual in the population at large of identical race, sex, and age and with as many other near matching characteristics as the existing data can provide. We could then compare the incidence of coffee drinkers in the cancer database with the incidence in the matching group of case controls.
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