In Daubert v. Merrell Dow Pharmaceuticals, Inc., the United States Supreme Court established a new method of assessing the admissibility of expert testimony in federal courts. The opinion and two subsequent opinions, General Electric Co. v. Joiner and Kumho Tire Co. v. Carmichael, have had a profound impact on civil litigation in the United States. Parties now routinely challenge the admissibility of the opposing expert’s testimony. This has led to the exclusion of experts in hundreds, possibly thousands, of cases. Given this substantial impact, it is perhaps surprising that considerable confusion still persists concerning exactly how trial courts should think about the decision to admit or exclude expert testimony. In this Article, we argue that much of the confusion exists because of the unresolved relationship between the admissibility of expert testimony on the one hand and the sufficiency of the scientific evidence to support a plaintiff verdict on the other hand. We argue that the best way to clarify the issue is to appreciate that most admissibility decisions regarding expert testimony are best thought of as sufficiency judgments about the scientific evidence supporting the expert’s testimony. We not only believe this is a better approach, we also believe that a close reading of opinions reveals that, in fact, many courts do adopt a sufficiency approach when making admissibility rulings.
An important tenet that is embedded in our discussion requires identification before we proceed. Any assessment of causation involves an inferential process from evidence to the causation conclusion. Causation, unlike, for example, the presence of another human being, is not something we observe directly but rather is an inference from what may be very strong or very weak circumstantial evidence. This principle is an important foundation for our claim that Daubert assessments frequently entail consideration of the circumstantial evidence—the science proffered by the plaintiff’s expert—and whether that evidence is sufficient to justify an inference of causation.
