Strength, causation

Because the British group applied extensively their statistical method to determine causation of large interindividual pharmacokinetic variations without describing its strengths and weaknesses, others have attempted to assess critically the application of multiple regression analysis for this particular purpose (31,32) While this statistical method has great potential, it requires considerable modification beyond its initial applications in this area (27-29), if that potential is to be realized (H,32). Thus far, its applications in pharmacokinetics (27-29) have been disappointing because those who have employed it neither formulated nor addressed, much less demonstrated fulfillment of, several fundamental assumptions inherent in its use ( 1, 32). 

The propriety of this kind of mental leaping is one of the most controversial aspects of toxic tort and occupational disease cases, where causation often cannot be properly formulated as a yes-or-no fact. Instead, parties rely on evidence of increased risk or enhanced probability of disease which may or may not be attributable to defendant s conduct. The inquiry becomes one of the existence and magnitude of a fact probability. Therefore, understanding the dual nature of probability, as both a factual statistical quantity (fact probability) and a measure of strength of belief (belief probability), becomes important. Unfortunately, fact probability and belief probability have not been kept analytically distinct. Courts have collapsed the requirements for burden of production and burden of persuasion into one test that blurs plaintiff s twofold task of defining not only the facts or elements to be proved but also the amount of credence to be accorded a fact in support of a finding. When a judge tells a jury that plaintiff must show that causation is more likely than not, she/he risks confusion. Does she/he mean that the fact of causation which plaintiff must prove (burden of production) is not traditional true-or-false (100% vs. 0%)... 

Here then are nine different viewpoints flom all of which we should study association before we cry causation. What I do not believe—and this has been suggested—that we can usefully lay down some hard-and-fast rules of evidence that must be obeyed before we can accept cause and effect. None of my nine viewpoints can bring indisputable evidence for or against the cause-and-effect hypothesis and none can be required as a sine qua non. What they can do, with greater or less strength, is to help us to make up our minds on the fundamental question—is there any other way of explaining the set of facts before us, is there any other answer equally, or more, likely than cause and effect ... 

The appropriate extent of analysis is depedent on the seriousness of the AE and the strength of evidence of drug candidate causation. 

Table 7.2 Strength of Research Designs Used to Determine Causation...

One of the strengths of the STS model is the notion that the four subsystems share joint causation , such that changes in one subsystem can impact other subsystans. As such, consideration of the entire systan must be made when changes in any one... 

In the context of medical causation. Sir Austin Bradford Hill, suggested in 1965 that to imply causation from the observation of association we should consider its (1) strength, (2) consistency, (3) specificity - the restriction to specific conditions, (4) temporality - the order of events, (5) dose-response relationship, (6) theoretical plausibility, and (7) coherence - the consistency with other related phenomena. Although these guidelines were presented in the context of medicine and epidemiology, it would be very usefiil to keep these necessary conditions for causality in mind when evaluating crash causation on the basis of statistical associations. 

---