Vigorous debate is a characteristic of modern scientific philosophy, no less in epidemiology than in other area (Rothman, 1988).
Perhaps the most important common thread that emerges from the debated philosophies is Hume's legacy that proof is impossible in empiric science. This simple fact is especially important to epidemiologists, who often face thecriticism that proof is impossible in epidemiology, with the implication that it is possible in other scientific disciplines. Such criticism may stem from a view that experiments are the definitive source of scientific knowledge. Such a view is mistaken on at least two counts. First, the nonexperimental nature of a science does not prec1ude impressive scientific discoveries; the myriad examplesinclude plate tectonics, the evolution of species, planets orbiting other stars, and the effects of cigarette smoking on human health. Even when they are possible, experiments (including randomized trials) do not provide anything approaching proof and in fact may be controversial, contradictory, or irreproducible. The cold-fusion debacle demonstrates well that neither physical nor experimental scienceis immune to such problems (Taubes, 1993).
Some experimental scientists hold that epidemiologic relations are only suggestive and believe that detailed laboratory study of mechanisms within single individuals can reveal cause-effect relations with certainty. This view overlooks the fact that all relations are suggestive in exactly the manner discussed by Hume: Even the most careful and detailedmechanistic dissection ofindividua1 events cannot provide more than associations, albeit at a finer level. Laboratory studies often involve a degree of observer control that cannot be approached in epidemiology; it is only this control, not the level of observation, that can strengthen the inferences from laboratory studies. And again, such control is no guarantee against error.
All of thefruits of scientific work, in epidemiology or other disciplines, are at best only tentative formulations of a description of nature, even when the work itself is carried out without mistakes. The tentativeness of our knowledge does not prevent practical applications, but it should keep us skeptical and critical, not only of everyone else's work but of our own as well.
CAUSAL INFERENCE INEPIDEMIOLOGY
Biologic knowledge about epidemiologic hypotheses is often scant, making the hypotheses themselves at times little more than vague statements of causal association between exposure and disease, such as "smoking causes cardiovascular disease." These vague hypotheses have only vague consequences that can be difficult to test. To cope with this vagueness, epidemiologists usually focus ontesting the negation of the causal hypothesis, that is, the null hypothesis that the exposure does not have a causal relation to disease. Then, any observed association can potentially refute the hypothesis, subject to the assumption (auxiliary hypothesis) that biases are absent.
Testing Competing Epidemiologic Theories
If the causal mechanism is stated specifically enough, epidemiologicobservations can provide crucial tests of competing non-null causal hypotheses. For example, when toxic shock syndrome was first studied, there were two competing hypotheses about the origin of the toxin. Under one hypothesis, the toxin was a chemical in the tampon, so that women using tampons were exposed to the toxin directly from the tampon. Under the other hypothesis, the tampon acted as a culturemedium for staphylococci that produced the toxin. Both hypotheses explained the relation of toxic shock occurrence to tampon use. The two hypotheses, however, lead to opposite predictions about the relation between the frequency of changing tampons and the risk of toxic shock. Under the hypothesis of a chemical intoxication, more frequent changing of the tampon would lead to more exposure to...