Ruling Out Bias & Confounding is Necessary to Evaluate Expert Witness Causation Opinions

In 2000, Congress amended the Federal Rules of Evidence to clarify, among other things, that Rule 702 had grown past the Supreme Court’s tentative, preliminary statement in Daubert, to include over a decade and half of further judicial experience and scholarly comment. One point of clarification in the 2000 amendments, carried forward since, was that expert witness testimony is admissible only if “the testimony is based on sufficient facts or data.” Rule 702(b). In other words, an expert witness’s opinions could fail the legal requirement of reliability and validity by lacking sufficient facts or data.

The American Law Institute (ALI), in its 2010 revision to The Restatement of Torts, purported to address the nature and quantum of evidence for causation in so-called toxic tort cases as a matter of substantive law only, without addressing admissibility of expert witness opinion testimony, by noting that the Restatement did “not address any other requirements for the admissibility of an expert witness’s testimony, including qualifications, expertise, investigation, methodology, or reasoning.” Restatement (Third) of Torts: Liability for Physical and Emotional Harm § 28, cmt. E (2010). The qualifying language seems to have come from a motion advanced by ALI member Larry S. Stewart.

The Restatement, however, was not faithful to its own claim; nor could it be. Rule 702(b) made sufficiency an explicit part of the admissibility calculus in 2000. The ALI should have known better to claim that its Restatement would not delve, and had not wandered, into the area of expert witness admissibility. The strategic goal for ignoring a key part of Rule 702 seems to have been to redefine expert witness reliability and validity as a “sufficiency” or “weight of the evidence” question, which the trial court was required to leave to the finder of fact (usually a lay jury) to resolve. The Restatement’s pretense to avoid addressing the admissibility of expert witness opinion turns on an incorrect assumption that sufficiency plays no role in judicial gatekeeping of opinion testimony.

At the time of the release of the Restatement (Third) of Torts: Liability for Physical and Emotional Harm, one of its Reporters, Michael D. Green, published an article in Trial, the glossy journal of the Association of Trial Lawyers of America (now known by the self-congratulatory name of the American Association of Justice), the trade organization for the litigation industry in the United States. Professor Green’s co-author was Larry S. Stewart, a former president of the plaintiffs’ lawyers’ group, and the ALI member who pressed the motion that led to the Comment E language quoted above. Their article indecorously touted the then new Restatement as a toolbox for plaintiffs’ lawyers.1

According to Green and Stewart, “Section 28, comment c [of the Restatement], seeks to clear the air.” Green at 46. These authors suggest that the Restatement sought to avoid “bright-line rules,” by recognizing that causal inference is a

matter of informed judgment, not scientific certainty; scientific analysis is informed by numerous factors (commonly known as the Hill criteria); and, in some cases, reasonable scientists can come to differing conclusions.”

Id.

There are several curious aspects to these pronouncements. First, the authors are conceding that the comment e caveat was violated because the Hill criteria certainly involve the causation expert witness’s methodology and reasoning. Second, the authors’ claim to have avoided “bright-line” rules is muddled when they purport to bifurcate “informed judgment” from “scientific certainty.” The latter phrase, “scientific certainty” is not a requirement in science or the law, which makes the comparison with informed judgment confusing. Understandably, Green and Stewart wished to note that in some cases, scientists could reasonably come to different conclusions about causation from a given data set, but their silence about the many cases in which scientists, outside the courtroom, do not reach the causal conclusion contended for by party advocate expert witnesses, is telling, given the obvious pro-litigation bias of their audience.

Perhaps the most problematic aspect of the authors’ approach to causal analysis is their reductionist statement that “scientific analysis is informed by numerous factors (commonly known as the Hill criteria).” The nine Hill criteria, to be sure, are important, but they follow an assessment whether the pre-requisites for the criteria have been met,2 namely an “association between two variables, perfectly clear-cut and beyond what we would care to attribute to the play of chance.”3

The problematic aspects of this litigation-industry magazine article raise the question whether the Restatement itself similarly provides erroneous guidance. The relevant discussion occurs in Chapter 5, on “Factual Cause, § 28 Comment c (3) General Causation. At one place, the comment seems to elevate the Hill criteria to the entire relevant consideration:

Observational group studies are subject to a variety of errors — sampling error, bias, and confounding — and may, as a result, find associations that are spurious and not causal. Only after an evaluative judgment, based on the Hill criteria, that the association is likely to be causal rather than spurious, is a study valid evidence of general causation and specific causation.”

Restatement at 449b.

This passage, like the Green and Stewart article, appears to treat the Hill criteria as the end-all of the evaluative judgment, which leaves out the need to assess and eliminate “sampling error, bias, and confounding” before proceeding to measure the available evidence against the Hill criteria. The first sentence, however, does suggest that addressing sampling error, bias, and confounding is part of causal inference, at least if spurious associations are to be avoided. Indeed, earlier in comment c, the reporters describe the examination of an association as explained by random error or bias as scientifically required:

when epidemiology finds an association, the observational (rather than experimental) nature of these studies requires an examination of whether the association is truly causal or spurious and due to random error or deficiencies in the study (bias).”

Restatement at 440b (emphasis added). This crucial explanation was omitted from the Green and Stewart article.

An earlier draft of comment c offered the following observation:

Epidemiologists use statistical methods to estimate the range of error that sampling error could produce; assessing the existence and impact of biases and uncorrected confounding is usually qualitative. Whether an inference of causation based on an association is appropriate is a matter of informed judgment, not scientific inquiry, as is a judgment whether a study that finds no association is exonerative or inconclusive.”

Fortunately, this observation was removed in the drafting process. The reason for the deletion is unclear, but its removal was well advised. The struck language would have been at best misleading when it suggests that the assessment of bias and confounding is “usually qualitative.” Elimination of confounding is the goal of multivariate analyses such as logistic regression and propensity score matching models, among other approaches, all of which are quantitative methods. Assessing bias quantitatively has been the subject of book-length treatment in the field of epidemiology.4

In comment c as published, the Reporters acknowledged that confounding can be identified and analyzed:

The observational nature of epidemiologic studies virtually always results in concerns about the results being skewed by biases or unidentified confounders. * * * Sometimes potential confounders can be identified and data gathered that permits analysis of whether confounding exists. Unidentified confounders, however, cannot be analyzed. Often potential biases can be identified, but assessing the extent to which they affected the study’s outcome is problematical. * * * Thus, interpreting the results of epidemiologic studies requires informed judgment and is subject to uncertainty. Unfortunately, contending adversarial experts, because of the pressures of the adversarial system, rarely explore this uncertainty and provide the best, objective assessment of the scientific evidence.”

Restatement at 448a.

It would be a very poorly done epidemiologic study that fails to identify and analyze confounding variables in a multivariate analysis. The key question will be whether the authors have done this analysis with due care, and with all the appropriate co-variates to address confounding thoroughly. The Restatement comment acknowledges that expert witnesses in the our courtrooms often fail to explore the uncertainty created by bias and confounding. Given the pressure on those witnesses claiming causal associations, we might well expect that this failure will not be equally distributed among all expert witnesses.


1 Michael D. Green & Larry S. Stewart, “The New Restatement’s Top 10 Tort Tools,” Trial 44 (April 2010) [cited as Green]. See “The Top Reason that the ALI’s Restatement of Torts Should Steer Clear of Partisan Conflicts.”

2 See Frank C. Woodside, III & Allison G. Davis, “The Bradford Hill Criteria: The Forgotten Predicate,” 35 Thomas Jefferson L. Rev. 103 (2013); see also Woodside & Davis on the Bradford Hill Considerations(Aug. 23, 2013).

3 Austin Bradford Hill, “The Environment and Disease: Association or Causation?” 58 Proc. Royal Soc’y Med. 295 (1965).

4 See, e.g., Timothy L. Lash, Matthew P. Fox, and Aliza K. Fink, Applying Quantitative Bias Analysis to Epidemiologic Data (2009).

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