TORTINI

For your delectation and delight, desultory dicta on the law of delicts.

Archives »

Counter Cancel Culture – The NAS Conference on Irreproducibility

February 9th, 2020

“The meaning of the world is the separation of wish and fact.”  Kurt Gödel

Back in October 2019, David Randall, the Director of Research, of the National Association of Scholars, contacted me to ask whether I would be interested in presenting at a conference, to be titled “Fixing Science: Practical Solutions for the Irreproducibility Crisis.” David explained that the conference would be aimed at a high level consideration of whether such a crisis existed, and if so, what salutary reforms might be implemented.

As for the character and commitments of the sponsoring organizations, David was candid and forthcoming. I will quote him, without his permission, and ask his forgiveness later:

“The National Association of Scholars is taken to be conservative by many scholars; the Independent Institute is (broadly speaking) in the libertarian camp. The NAS is open to but currently agnostic about the degree of human involvement in climate change. The Independent Institute I take to be institutionally skeptical of consensus climate change theory–e.g., they recently hosted Willie Soon for lecture. A certain number of speakers prefer not to participate in events hosted by institutions with these commitments.”

To me, the ask was for a presentation on how the so-called replication crisis, or the irreproducibility crisis, affected the law. This issue was certainly one I have had much occasion to consider. Although I am aware of the “adjacency” arguments made by some that people should be mindful of whom they align with, I felt that nothing in my participation would compromise my own views or unduly accredit institutional positions of the sponsors.

I was flattered by the invitation, but I did some due diligence on the sponsoring organizations. I vaguely recalled the Independent Institute from my more libertarian days, but the National Association of Scholars (NAS, not to be confused with Nathan A. Schachtman) was relatively unknown to me. A little bit of research showed that the NAS had a legitimate interest in the irreproducibility crisis. David Randall had written a monograph for the organization, which was a nice summary of some of the key problems. The Irreproducibility Crisis of Modern Science: Causes, Consequences,and the Road to Reform (2018).

On other issues, the NAS seemed to live up to its description as “an organization of scholars committed to higher education as the catalyst of American freedom.” I listened to some of the group’s podcasts, Curriculum Vitae, and browsed through its publications. I found myself agreeing with many positions articulated by or through the NAS, and disagreeing with a few positions very strongly.

In looking over the list of other invited speakers, I saw great diversity of view points and approaches, One distinguished speaker, Daniele Fanelli, had criticized the very notion that there was a reproducibility crisis. In the world of statistics, there were strong defenders of statistical tests, and vociferous critics. I decided to accept the invitation, not because I was flattered, but because the replication issue was important, and I believed that I could add something to the discussion before an audience of professional scientists, statisticians, and educated lay persons. In writing to David Randall to accept the invitation, I told him that with respect to the climate change issues, I was not at all put off by healthy skepticism in the face all dogmas. Every dogma will have its day.

I did not give any further consideration to the political aspect of the conference until early January, when I received an email from a scientist, Lenny Teytelman, Ph.D., the C.E.O. of a company protocols.io, which addresses reproducibility issues. Dr Teytelman’s interest in improving reproducibility seemed quite genuine, but he wrote to express his deep concern about the conference and the organizations that were sponsoring it.

Perhaps a bit pedantically, he cautioned me that the NAS was not the National Academy of Sciences, a confusion that never occurred to me because the National Academies has been known as the National Academies of Science, Engineering and Medicine for several years now. Dr. Teytelman’s real concern seemed to be that the NAS is a “‘politically conservative advocacy group’.” (The internal scare quotes were Teytelman’s, but I was not afraid.) According to Dr. Teytelman, the NAS sought to undermine climate science and environmental protection by advancing a call for more reproducible science. He pointed me to what he characterized as an exposé on NAS, in Undark,1 and he cautioned me that the National Association of Scholars’ work is “dangerous.” Finally, Dr. Teytelman urged me to reconsider my decision to participate in the conference.

I did reconsider my decision, but reaffirmed it in an email I sent back to Dr. Teytelman. I realized that I could be wrong, in which case, I would eat my words, confident that they would be most digestible:

Dear Dr Teytelman,

Thank you for your note. I was aware of the piece on Undark’s website, as well as the difference between the NAS and the NASEM. I don’t believe anyone involved in science education would likely to be confused between the two organizations. A couple of years ago, I wrote a teaching module on biomedical causation for the National Academies. This is my first presentation at the request of the NAS, and frankly I am honored by the organization’s request that I present at its conference.

I have read other materials that have been critical of the NAS and its publications on climate change and other issues. I know that there are views of the organization from which I would dissent, but I do not see my disagreement on some issues as a reason not to attend, and present at a conference on an issue of great importance to the legal system.

I am hardly an expert on climate change issues, and that is my failing. Most of my professional work involves health effects regulation and litigation. If the NAS has advanced sophistical arguments against a scientific claim, then the proper antidote will be to demonstrate its fallacious reasoning and misleading marshaling of evidence. I should think, however, as someone interested in improving the reproducibility of scientific research, you will agree that there is much common ground for discussion and reform of scientific practice, on a broader arrange [sic] of issues than climate change.

As for the political ‘conservatism’, of the organization, I am not sure why that is a reason to eschew participation in a conference that should be of great importance to people of all political views. My own politics probably owe much to the influence of Michael Oakeshott, which puts me in perhaps the smallest political tribe of any in the United States. If conservatism means antipathy to post-modernism, identity politics, political orthodoxies, and assaults on Enlightenment values and the Rule of Law, then count me in.

In any event, thanks for your solicitude. I think I can participate and return with my soul intact.

All the best.

Nathan

To his credit, Dr. Teytelman tenaciously continued. He acknowledged that the political leanings of the organizers were not a reason to boycott, but he politely pressed his case. We were now on a first name basis:

Dear Nathan,

I very much applaud all efforts to improve the rigour of our science. The problem here is that this NAS organization has a specific goal – undermining the environmental protection and denying climate change. This is why 7 out of the 21 speakers at the event are climate change deniers. [https://docs.google.com/spreadsheets/d/136FNLtJzACc6_JbbOxjy2urbkDK7GefRZ/edit?usp=sharing] And this isn’t some small fringe effort to be ignored. Efforts of this organization and others like them have now gotten us to the brink of a regulatory change at the United States Environmental Protection Agency which can gut the entire EPA (see a recent editorial against this I co-authored). This conference is not a genuine effort to talk about reproducibility. The reproducibility part is a clever disguise for pushing a climate change denialism agenda.

Best,

Lenny

I looked more carefully at Lenny’s spreadsheet, and considered the issue afresh. We were both pretty stubborn:

Dear Lenny,

Thank you for this information. I will review with interest.

I do not see that the conference is primarily or even secondarily about climate change vel non. There are two scientists, Trafimow and Wasserstein with whom I have some disagreements about statistical methodology. Tony Cox and Stan Young, whatever their political commitments or views on climate change may be, are both very capable statisticians, from whom I have learned a great deal. The conference should be a lively conversation about reproducibility, not about climate change. Given your interests and background, you should go.

I believe that your efforts here are really quite illiberal, although they are in line with the ‘cancel culture’, so popular on campuses these days.

Forty three years ago, I entered a Roman Catholic Church to marry the woman I love. There were no lightning bolts or temblors, even though I was then and I am now an atheist. Yes, I am still married to my first wife. Although I share the late Christopher Hitchins’ low view of the Catholic Church, somehow I managed to overcome my antipathy to being married in what some would call a house of ill repute. I even manage to agree with some Papist opinions, although not for the superstitious ‘reasons’ Papists embrace.

If I could tolerate the RC Church’s dogma for a morning, perhaps you could put aside the dichotomous ‘us and them’ view of the world and participate in what promises to be an interesting conference on reproducibility?

All the best.

Nathan

Lenny kindly acknowledged my having considered his issues, and wrote back a nice note, which I will quote again in full without permission, but with the hope that he will forgive me and even acknowledge that I have given his views an airing in this forum.

Hi Nathan,

We’ll have to agree to disagree. I don’t want to give a veneer of legitimacy to an organization whose goal is not improving reproducibility but derailing EPA and climate science.

Warmly,

Lenny

The business of psychoanalyzing motives and disparaging speakers and conference organizers is a dangerous business for several reasons. First motives can be inscrutable. Second, they can be misinterpreted. And third, they can be mixed. When speaking of organizations, there is the further complication of discerning a corporate motive among the constituent members.

The conference was an exciting, intellectually challenging event, which took place in Oakland, California, on February 7 and 8. I can report back to Lenny that his characterizations of and fears about the conference were unwarranted. While there were some assertions of climate change skepticism made with little or no evidence, the evidence-based presentations essentially affirmed climate change and sought to understand its causes and future course in a scientific way. But climate change was not why I went to this conference. On the more general issue of reform of scientific procedures and methods, we had open debates, some agreement on important principles, and robust and reasoned disagreement.

Lenny, you were correct that the NAS should not be ignored, but you should have gone to the meeting and participated in the conversation.

1 Michael Schulson, “A Remedy for Broken Science, Or an Attempt to Undercut It?” Undark (April 18, 2018).

Posted in Cognitive Biases, Conflicts of Interest, Scientific Evidence, Scientific Misconduct, statistical evidence | Comments Off on Counter Cancel Culture – The NAS Conference on Irreproducibility

Judicial Gatekeeping Cures Claims That Viagra Can Cause Melonoma

January 24th, 2020

The phosphodiesterases 5 inhibitor medications (PDE5i) seem to arouse the litigation propensities of the lawsuit industry. The PDE5i medications (sildenafil, tadalafil, etc.) have multiple indications, but they are perhaps best known for their ability to induce penile erections, which in some situations can be a very useful outcome.

The launch of Viagra in 1998 was followed by litigation that claimed the drug caused heart attacks, and not the romantic kind. The only broken hearts, however, were those of the plaintiffs’ lawyers and their expert witnesses who saw their litigation claims excluded and dismissed.[1]

Then came claims that the PDE5i medications caused non-arteritic anterior ischemic optic neuropathy (“NAION”), based upon a dubious epidemiologic study by Dr. Gerald McGwin. This litigation demonstrated, if anything, that while love may be blind, erections need not be.[2] The NAION cases were consolidated in a multi-district litigation (MDL) in front of Judge Paul Magnuson, in the District of Minnesota. After considerable back and forth, Judge Manguson ultimately concluded that the McGwin study was untrustworthy, and the NAION claims were dismissed.[3]

In 2014, the American Medical Association’s internal medicine journal published an observational epidemiologic study of sildenafil (Viagra) use and melanoma.[4] The authors of the study interpreted their study modestly, concluding:

“[s]ildenafil use may be associated with an increased risk of developing melanoma. Although this study is insufficient to alter clinical recommendations, we support a need for continued investigation of this association.”

Although the Li study eschewed causal conclusions and new clinical recommendations in view of the need for more research into the issue, the litigation industry filed lawsuits, claiming causality.[5]

In the new natural order of things, as soon as the litigation industry cranks out more than a few complaints, an MDL results, and the PDE5i – melanoma claims were no exception. By spring 2016, plaintiffs’ counsel had collected ten cases, a minion, sufficient for an MDL.[6] The MDL plaintiffs named the manufacturers of sildenafil and tadalafil, two of the more widely prescribed PDEi5 medications, on behalf of putative victims.

While the MDL cases were winding their way through discovery and possible trials, additional studies and meta-analyses were published. None of the subsequent studies, including the systematic reviews and meta-analyses, concluded that there was a causal association. Most scientists who were publishing on the issue opined that systematic error (generally confounding) prevented a causal interpretation of the data.[7]

Many of the observational studies found statistically significantly increased relative risks about 1.1 to 1.2 (10 to 20%), typically with upper bounds of 95% confidence intervals less than 2.0. The only scientists who inferred general causation from the available evidence were those who had been recruited and retained by plaintiffs’ counsel. As plaintiffs’ expert witnesses, they contended that the Li study, and the several studies that became available afterwards, collectively showed that PDE5i drugs cause melanoma in humans.

Not surprisingly, given the absence of any non-litigation experts endorsing the causal conclusion, the defendants challenged plaintiffs’ proffered expert witnesses under Federal Rule of Evidence 702. Plaintiffs’ counsel also embraced judicial gatekeeping and challenged the defense experts. The MDL trial judge, the Hon. Richard Seeborg, held hearings with four days of viva voce testimony from four of plaintiffs’ expert witnesses (two on biological plausibility, and two on epidemiology), and three of the defense’s experts. Last week, Judge Seeborg ruled by granting in part, and denying in part, the parties’ motions.[8]

The Decision

The MDL trial judge’s opinion is noteworthy in many respects. First, Judge Richard Seeborg cited and applied Rule 702, a statute, and not dicta from case law that predates the most recent statutory version of the rule. As a legal process matter, this respect for judicial process and the difference in legal authority between statutory and common law was refreshing. Second, the judge framed the Rule 702 issue, in line with the statute, and Ninth Circuit precedent, as an inquiry whether expert witnesses deviated from the standard of care of how scientists “conduct their research and reach their conclusions.”[9]

Biological Plausibility

Plaintiffs proffered three expert witnesses on biological plausibility, Drs. Rizwan Haq, Anand Ganesan, and Gary Piazza. All were subject to motions to exclude under Rule 702. Judge Seeborg denied the defense motions against all three of plaintiffs’ plausibility witnesses.[10]

The MDL judge determined that biological plausibility is neither necessary nor sufficient for inferring causation in science or in the law. The defense argued that the plausibility witnesses relied upon animal and cell culture studies that were unrealistic models of the human experience.[11] The MDL court, however, found that the standard for opinions on biological plausibility is relatively forgiving, and that the testimony of all three of plaintiffs’ proffered witnesses was admissible.

The subjective nature of opinions about biological plausibility is widely recognized in medical science.[12] Plausibility determinations are typically “Just So” stories, offered in the absence of hard evidence that postulated mechanisms are actually involved in a real causal pathway in human beings.

Causal Association

The real issue in the MDL hearings was the conclusion reached by plaintiffs’ expert witnesses that the PDE5i medications cause melanoma. The MDL court did not have to determine whether epidemiologic studies were necessary for such a causal conclusion. Plaintiffs’ counsel had proffered three expert witnesses with more or less expertise in epidemiology: Drs. Rehana Ahmed-Saucedo, Sonal Singh, and Feng Liu-Smith. All of plaintiffs’ epidemiology witnesses, and certainly all of defendants’ experts, implicitly if not explicitly embraced the proposition that analytical epidemiology was necessary to determine whether PDE5i medications can cause melanoma.

In their motions to exclude Ahmed-Saucedo, Singh, and Liu-Smith, the defense pointed out that, although many of the studies yielded statistically significant estimates of melanoma risk, none of the available studies adequately accounted for systematic bias in the form of confounding. Although the plaintiffs’ plausibility expert witnesses advanced “Just-So” stories about PDE5i and melanoma, the available studies showed an almost identical increased risk of basal cell carcinoma of the skin, which would be explained by confounding, but not by plaintiffs’ postulated mechanisms.[13]

The MDL court acknowledged that whether epidemiologic studies “adequately considered” confounding was “central” to the Rule 702 inquiry. Without any substantial analysis, however, the court gave its own ipse dixit that the existence vel non of confounding was an issue for cross-examination and the jury’s resolution.[14] Whether there was a reasonably valid association between PDE5i and melanoma was a jury question. This judicial refusal to engage with the issue of confounding was one of the disappointing aspects of the decision.

The MDL court was less forgiving when it came to the plaintiffs’ epidemiology expert witnesses’ assessment of the association as causal. All the parties’ epidemiology witnesses invoked Sir Austin Bradford Hill’s viewpoints or factors for judging whether associations were causal.[15] Although they embraced Hill’s viewpoints on causation, the plaintiffs’ epidemiologic expert witnesses had a much more difficult time faithfully applying them to the evidence at hand. The MDL court concluded that the plaintiffs’ witnesses deviated from their own professional standard of care in their analysis of the data.[16]

Hill’s first enumerated factor was “strength of association,” which is typically expressed epidemiologically as a risk ratio or a risk difference. The MDL court noted that the extant epidemiologic studies generally showed relative risks around 1.2 for PDE5i and melanoma, which was “undeniably” not a strong association.[17]

The plaintiffs’ epidemiology witnesses were at sea on how to explain away the lack of strength in the putative association. Dr. Ahmed-Saucedo retreated into an emphasis on how all or most of the studies found some increased risk, but the MDL court correctly found that this ruse was merely a conflation of strength with consistency of the observed associations. Dr. Ahmed-Saucedo’s dismissal of the importance of a dose-response relationship, another Hill factor, as unimportant sealed her fate. The MDL court found that her Bradford Hill analysis was “unduly results-driven,” and that her proffered testimony was not admissible.[18] Similarly, the MDL court found that Dr. Feng Liu-Smith similarly conflated strength of association with consistency, which error was too great a professional deviation from the standard of care.[19]

Dr. Sonal Singh fared no better after he contradicted his own prior testimony that there is an order of importance to the Hill factors, with “strength of association,” at or near the top. In the face of a set of studies, none of which showed a strong association, Dr. Singh abandoned his own interpretative principle to suit the litigation needs of the case. His analysis placed the greatest weight on the Li study, which had the highest risk ratio, but he failed to advance any persuasive reason for his emphasis on one of the smallest studies available. The MDL court found that Dr. Singh’s claim to have weighed strength of association heavily, despite the obvious absence of strong associations, puzzling and too great an analytical gap to abide.[20]

Judge Seeborg thus concluded that while the plaintiffs’ expert witness could opine that there was an association, which was arguably plausible, they could not, under Rule 702, contend that the association was causal. In attempting to advance an argument that the association met Bradford Hill’s factors for causality, the plaintiffs’ witnesses had ignored, misrepresented, or confused one of the most important factors, strength of the association, in a way that revealed their analyses to be result driven and unfaithful to the methodology they claimed to have followed. Judge Seeborg emphasized a feature of the revised Rule 702, which often is ignored by his fellow federal judges:[21]

“Under the amendment, as under Daubert, when an expert purports to apply principles and methods in accordance with professional standards, and yet reaches a conclusion that other experts in the field would not reach, the trial court may fairly suspect that the principles and methods have not been faithfully applied. See Lust v. Merrell Dow Pharmaceuticals, Inc., 89 F.3d 594, 598 (9th Cir. 1996). The amendment specifically provides that the trial court must scrutinize not only the principles and methods used by the expert, but also whether those principles and methods have been properly applied to the facts of the case.”

Given that the plaintiffs’ witnesses purported to apply a generally accepted methodology, Judge Seeborg was left to question why they would conclude causality when no one else in their field had done so.[22] The epidemiologic issue had been around for several years, and addressed not just in observational studies, but systematically reviewed and meta-analyzed. The absence of published causal conclusions was not just an absence of evidence, but evidence of absence of expert support for how plaintiffs’ expert witnesses applied the Bradford Hill factors.

Reliance Upon Studies That Did Not Conclude Causation Existed

Parties challenging causal claims will sometimes point to the absence of a causal conclusion in the publication of individual epidemiologic studies that are the main basis for the causal claim. In the PDE5i-melanoma cases, the defense advanced this argument unsuccessfully. The MDL court rejected the defense argument, based upon the absence of any comprehensive review of all the pertinent evidence for or against causality in an individual study; the study authors are mostly concerned with conveying the results of their own study.[23] The authors may have a short discussion of other study results as the rationale for their own study, but such discussions are often limited in scope and purpose. Judge Seeborg, in this latest round of PDE5i litigation, thus did not fault plaintiffs’ witnesses’ reliance upon epidemiologic or mechanistic studies, which individually did not assert causal conclusions; rather it was the absence of causal conclusions in systematic reviews, meta-analyses, narrative reviews, regulatory agency pronouncements, or clinical guidelines that ultimately raised the fatal inference that the plaintiffs’ witnesses were not faithfully deploying a generally accepted methodology.

The defense argument that pointed to the individual epidemiologic studies themselves derives some legal credibility from the Supreme Court’s opinion in General Electric Co. v. Joiner, 522 U.S. 136 (1997). In Joiner, the SCOTUS took plaintiffs’ expert witnesses to task for drawing stronger conclusions than were offered in the papers upon which they relied. Chief Justice Rehnquist gave considerable weight to the consideration that the plaintiffs’ expert witnesses relied upon studies, the authors of which explicitly refused to interpret as supporting a conclusion of human disease causation.[24]

Joiner’s criticisms of the reliance upon studies that do not themselves reach causal conclusions have gained a foothold in the case law interpreting Rule 702. The Fifth Circuit, for example, has declared:[25]

“It is axiomatic that causation testimony is inadmissible if an expert relies upon studies or publications, the authors of which were themselves unwilling to conclude that causation had been proven.”

This aspect of Joiner may properly limit the over-interpretation or misinterpretation of an individual study, which seems fine.[26] The Joiner case may, however, perpetuate an authority-based view of science to the detriment of requiring good and sufficient reasons to support the testifying expert witnesses’ opinions.  The problem with Joiner’s suggestion that expert witness opinion should not be admissible if it disagrees with the study authors’ discussion section is that sometimes study authors grossly over-interpret their data.  When it comes to scientific studies written by “political scientists” (scientists who see their work as advancing a political cause or agenda), then the discussion section often becomes a fertile source of unreliable, speculative opinions that should not be given credence in Rule 104(a) contexts, and certainly should not be admissible in trials. In other words, the misuse of non-rigorous comments in published articles can cut both ways.

There have been, and will continue to be, occasions in which published studies contain data, relevant and important to the causation issue, but which studies also contain speculative, personal opinions expressed in the Introduction and Discussion sections.  The parties’ expert witnesses may disagree with those opinions, but such disagreements hardly reflect poorly upon the testifying witnesses.  Neither side’s expert witnesses should be judged by those out-of-court opinions.  Perhaps the hearsay discussion section may be considered under Rule 104(a), which suspends the application of the Rules of Evidence, but it should hardly be a dispositive factor, other than raising questions for the reviewing court.

In exercising their gatekeeping function, trial judges should exercise care in how they assess expert witnesses’ reliance upon study data and analyses, when they disagree with the hearsay authors’ conclusions or discussions.  Given how many journals cater to advocacy scientists, and how variable the quality of peer review is, testifying expert witnesses should, in some instances,  have the expertise to interpret the data without substantial reliance upon, or reference to, the interpretative comments in the published literature.

Judge Seeborg sensibly seems to have distinguished between the absence of causal conclusions in individual epidemiologic studies and the absence of causal conclusions in any reputable medical literature.[27] He refused to be ensnared in the Joiner argument because:[28]

“Epidemiology studies typically only expressly address whether an association exists between agents such as sildenafil and tadalafil and outcomes like melanoma progression. As explained in In re Roundup Prod. Liab. Litig., 390 F. Supp. 3d 1102, 1116 (N.D. Cal. 2018), ‘[w]hether the agents cause the outcomes, however, ordinarily cannot be proven by epidemiological studies alone; an evaluation of causation requires epidemiologists to exercise judgment about the import of those studies and to consider them in context’.”

This new MDL opinion, relying upon the Advisory Committee Notes to Rule 702, is thus a more felicitous statement of the goals of gatekeeping.

Confidence Intervals

As welcome as some aspects of Judge Seeborg’s opinion are, the decision is not without mistakes. The district judge, like so many of his judicial colleagues, trips over the proper interpretation of a confidence interval:[29]

“When reviewing the results of a study it is important to consider the confidence interval, which, in simple terms, is the ‘margin of error’. For example, a given study could calculate a relative risk of 1.4 (a 40 percent increased risk of adverse events), but show a 95 percent ‘confidence interval’ of .8 to 1.9. That confidence interval means there is 95 percent chance that the true value—the actual relative risk—is between .8 and 1.9.”

This statement is inescapably wrong. The 95 percent probability attaches to the capturing of the true parameter – the actual relative risk – in the long run of repeated confidence intervals that result from repeated sampling of the same sample size, in the same manner, from the same population. In Judge Seeborg’s example, the next sample might give a relative risk point estimate 1.9, and that new estimate will have a confidence interval that may run from just below 1.0 to over 3. A third sample might turn up a relative risk estimate of 0.8, with a confidence interval that runs from say 0.3 to 1.4. Neither the second nor the third sample would be reasonably incompatible with the first. A more accurate assessment of the true parameter is that it will be somewhere between 0.3 and 3, a considerably broader range for the 95 percent.

Judge Seeborg’s error is sadly all too common. Whenever I see the error, I wonder whence it came. Often the error is in briefs of both plaintiffs’ and defense counsel. In this case, I did not see the erroneous assertion about confidence intervals made in plaintiffs’ or defendants’ briefs.

[1]  Brumley  v. Pfizer, Inc., 200 F.R.D. 596 (S.D. Tex. 2001) (excluding plaintiffs’ expert witness who claimed that Viagra caused heart attack); Selig v. Pfizer, Inc., 185 Misc. 2d 600 (N.Y. Cty. S. Ct. 2000) (excluding plaintiff’s expert witness), aff’d, 290 A.D. 2d 319, 735 N.Y.S. 2d 549 (2002).

[2]  “Love is Blind but What About Judicial Gatekeeping of Expert Witnesses? – Viagra Part I” (July 7, 2012); “Viagra, Part II — MDL Court Sees The Light – Bad Data Trump Nuances of Statistical Inference” (July 8, 2012).

[3]  In re Viagra Prods. Liab. Litig., 572 F.Supp. 2d 1071 (D. Minn. 2008), 658 F. Supp. 2d 936 (D. Minn. 2009), and 658 F. Supp. 2d 950 (D. Minn. 2009).

[4]  Wen-Qing Li, Abrar A. Qureshi, Kathleen C. Robinson, and Jiali Han, “Sildenafil use and increased risk of incident melanoma in US men: a prospective cohort study,” 174 J. Am. Med. Ass’n Intern. Med. 964 (2014).

[5]  See, e.g., Herrara v. Pfizer Inc., Complaint in 3:15-cv-04888 (N.D. Calif. Oct. 23, 2015); Diana Novak Jones, “Viagra Increases Risk Of Developing Melanoma, Suit Says,” Law360 (Oct. 26, 2015).

[6]  See In re Viagra (Sildenafil Citrate) Prods. Liab. Litig., 176 F. Supp. 3d 1377, 1378 (J.P.M.L. 2016).

[7]  See, e.g., Jenny Z. Wang, Stephanie Le , Claire Alexanian, Sucharita Boddu, Alexander Merleev, Alina Marusina, and Emanual Maverakis, “No Causal Link between Phosphodiesterase Type 5 Inhibition and Melanoma,” 37 World J. Men’s Health 313 (2019) (“There is currently no evidence to suggest that PDE5 inhibition in patients causes increased risk for melanoma. The few observational studies that demonstrated a positive association between PDE5 inhibitor use and melanoma often failed to account for major confounders. Nonetheless, the substantial evidence implicating PDE5 inhibition in the cyclic guanosine monophosphate (cGMP)-mediated melanoma pathway warrants further investigation in the clinical setting.”); Xinming Han, Yan Han, Yongsheng Zheng, Qiang Sun, Tao Ma, Li Dai, Junyi Zhang, and Lianji Xu, “Use of phosphodiesterase type 5 inhibitors and risk of melanoma: a meta-analysis of observational studies,” 11 OncoTargets & Therapy 711 (2018).

[8]  In re Viagra (Sildenafil Citrate) and Cialis (Tadalafil) Prods. Liab. Litig., Case No. 16-md-02691-RS, Order Granting in Part and Denying in Part Motions to Exclude Expert Testimony (N.D. Calif. Jan. 13, 2020) [cited as Opinion].

[9]  Opinion at 8 (“determin[ing] whether the analysis undergirding the experts’ testimony falls within the range of accepted standards governing how scientists conduct their research and reach their conclusions”), citing Daubert v. Merrell Dow Pharm., Inc. (Daubert II), 43 F.3d 1311, 1317 (9th Cir. 1995).

[10]  Opinion at 11.

[11]  Opinion at 11-13.

[12]  See Kenneth J. Rothman, Sander Greenland, and Timothy L. Lash, “Introduction,” chap. 1, in Kenneth J. Rothman, et al., eds., Modern Epidemiology at 29 (3d ed. 2008) (“no approach can transform plausibility into an objective causal criterion).

[13]  Opinion at 15-16.

[14]  Opinion at 16-17.

[15]  See Austin Bradford Hill, “The Environment and Disease: Association or Causation?” 58 Proc. Royal Soc’y Med. 295 (1965); see also “Woodside & Davis on the Bradford Hill Considerations” (April 23, 2013).

[16]  Opinion at 17 – 21.

[17]  Opinion at 18. The MDL court cited In re Silicone Gel Breast Implants Prod. Liab. Litig., 318 F. Supp. 2d 879, 893 (C.D. Cal. 2004), for the proposition that relative risks greater than 2.0 permit the inference that the agent under study “was more likely than not responsible for a particular individual’s disease.”

[18]  Opinion at 18.

[19]  Opinion at 20.

[20]  Opinion at 19.

[21]  Opinion at 21, quoting from Rule 702, Advisory Committee Notes (emphasis in Judge Seeborg’s opinion).

[22]  Opinion at 21.

[23]  See “Follow the Data, Not the Discussion” (May 2, 2010).

[24]  Joiner, 522 U.S. at 145-46 (noting that the PCB studies at issue did not support expert witnesses’ conclusion that PCB exposure caused cancer because the study authors, who conducted the research, were not willing to endorse a conclusion of causation).

[25]  Huss v. Gayden, 571 F.3d 442  (5th Cir. 2009) (citing Vargas v. Lee, 317 F.3d 498, 501-01 (5th Cir. 2003) (noting that studies that did not themselves embrace causal conclusions undermined the reliability of the plaintiffs’ expert witness’s testimony that trauma caused fibromyalgia); see also McClain v. Metabolife Internat’l, Inc., 401 F.3d 1233, 1247-48 (11th Cir. 2005) (expert witnesses’ reliance upon studies that did not reach causal conclusions about ephedrine supported the challenge to the reliability of their proffered opinions); Happel v. Walmart, 602 F.3d 820, 826 (7th Cir. 2010) (observing that “is axiomatic that causation testimony is inadmissible if an expert relies upon studies or publications, the authors of which were themselves unwilling to conclude that causation had been proven”).

[26]  In re Accutane Prods. Liab. Litig., 511 F. Supp. 2d 1288, 1291 (M.D. Fla. 2007) (“When an expert relies on the studies of others, he must not exceed the limitations the authors themselves place on the study. That is, he must not draw overreaching conclusions.) (internal citations omitted).

[27]  See Rutigliano v. Valley Bus. Forms, 929 F. Supp. 779, 785 (D.N.J. 1996), aff’d, 118 F.3d 1577 (3d Cir. 1997) (“law warns against use of medical literature to draw conclusions not drawn in the literature itself …. Reliance upon medical literature for conclusions not drawn therein is not an accepted scientific methodology.”).

[28]  Opinion at 14

[29]  Opinion at 4 – 5.

Posted in Causation, Confounding, Expert Witnesses, Meta-analysis, Rule 702, Scientific Evidence | Comments Off on Judicial Gatekeeping Cures Claims That Viagra Can Cause Melonoma

American Statistical Association – Consensus versus Personal Opinion

December 13th, 2019

Lawyers and judges pay close attention to standards, guidances, and consenus statements from respected and recognized professional organizations. Deviations from these standards may be presumptive evidence of malpractice or malfeasance in civil and criminal litigation, in regulatory matters, and in other contexts. One important, recurring situation arises when trial judges must act as gatekeepers of the admissibility of expert witness opinion testimony. In making this crucial judicial determination, judges will want to know whether a challenged expert witness has deviated from an accepted professional standard of care or practice.

In 2016, the American Statistical Association (ASA) published a consensus statement on p-values. The ASA statement grew out of a lengthy process that involved assembling experts of diverse viewpoints. In October 2015, the ASA convened a two-day meeting for 20 experts to meet and discuss areas of core agreement. Over the following three months, the participating experts and the ASA Board members continued their discussions, which led to the ASA Executive Committee’s approval of the statement that was published in March 2016.[1]

The ASA 2016 Statement spelled out six relatively uncontroversial principles of basic statistical practice.[2] Far from rejecting statistical significance, the six principles embraced statistical tests as an important but insufficient basis for scientific conclusions:

“3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.”

Despite the fairly clear and careful statement of principles, legal actors did not take long to misrepresent the ASA principles.[3] What had been a prescription about the insufficiency of p-value thresholds was distorted into strident assertions that statistical significance was unnecessary for scientific conclusions.

Three years after the ASA published its p-value consensus document, ASA Executive Director, Ronald Wasserstein, and two other statisticians, published an editorial in a supplemental issue of The American Statistician, in which they called for the abandonment of significance testing.[4] Although the Wasserstein’s editorial was clearly labeled as such, his essay introduced the special journal issue, and it appeared without disclaimer over his name, and his official status as the ASA Executive Director.

Sowing further confusion, the editorial made the following pronouncement:[5]

“The [2016] ASA Statement on P-Values and Statistical Significance stopped just short of recommending that declarations of ‘statistical significance’ be abandoned. We take that step here. We conclude, based on our review of the articles in this special issue and the broader literature, that it is time to stop using the term “statistically significant” entirely. Nor should variants such as ‘significantly different’, ‘p < 0.05’, and ‘nonsignificant’ survive, whether expressed in words, by asterisks in a table, or in some other way.”

The ASA is a collective body, and its ASA Statement 2016 was a statement from that body, which spoke after lengthy deliberation and debate. The language, quoted above, moves within one paragraph, from the ASA Statement to the royal “We,” who are taking the step of abandoning the term “statistically significant.” Given the unqualified use of the collective first person pronoun in the same paragraph that refers to the ASA, combined with Ronald Wasserstein’s official capacity, and the complete absence of a disclaimer that this pronouncement was simply a personal opinion, a reasonable reader could hardly avoid concluding that this pronouncement reflected ASA policy.

Your humble blogger, and others, read Wasserstein’s 2019 editorial as an ASA statement.[6] Although it is true that the 2019 paper is labeled “editorial,” and that the editorial does not describe a consensus process, there is no disclaimer such as is customary when someone in an official capacity publishes a personal opinion. Indeed, rather than the usual disclaimer, the Wasserstein editorial thanks the ASA Board of Directors “for generously and enthusiastically supporting the ‘p-values project’ since its inception in 2014.” This acknowledgement strongly suggests that the editorial is itself part of the “p-values project,” which is “enthusiastically” supported by the ASA Board of Directors.

If the editorial were not itself confusing enough, an unsigned email from “ASA <asamail@amstat.org>” was sent out in July 2019, in which the anonymous ASA author(s) takes credit for changing statistical guidelines at the New England Journal of Medicine:[7]

From: ASA <asamail@amstat.org>
Date: Thu, Jul 18, 2019 at 1:38 PM
Subject: Major Medical Journal Updates Statistical Policy in Response to ASA Statement
To: <XXXX>

The email is itself an ambiguous piece of evidence as to what the ASA is claiming. The email says that the New England Journal of Medicine changed its guidelines “in response to the ASA Statement on P-values and Statistical Significance and the subsequent The American Statistician special issue on statistical inference.” Of course, the “special issue” was not just Wasserstein’s editorial, but the 42 other papers. So this claim leaves open to doubt exactly what in the 2019 special issue the NEJM editors were responding to. Given that the 42 articles that followed Wasserstein’s editorial did not all agree with Wasserstein’s “steps taken,” or with each other, the only landmark in the special issue was the editorial over the name of the ASA’s Executive Director.

Moreover, a reading of the NEJM revised guidelines does not suggest that the journal’s editors were unduly influenced by the Wasserstein editorial or the 42 accompanying papers. The journal mostly responded to the ASA 2016 consensus paper by putting some teeth into its Principle 4, which dealt with multiplicity concerns in submitted manuscripts.  The newly adopted (2019) NEJM author guidelines do not take step out with Wasserstein and colleagues; there is no general prohibition on p-values or statements of “statistical significance.”

The confusion propagated by the Wasserstein 2019 editorial has not escaped the attention of other ASA officials. An editorial in the June 2019 issue of AmStat News, by ASA President Karen Kafadar, noted the prevalent confusion and uneasiness over the 2019 The American Statistician special issue, the lack of consensus, and the need for healthy debate.[8]

In this month’s issue of AmStat News, President Kafadar returned to the issue of the confusion over the 2019 ASA special issue of The American Statistician, in her “President’s Corner.” Because Executive Director Wasserstein’s editorial language about “we now take this step” is almost certainly likely to find its way into opportunistic legal briefs, Kafadar’s comments are worth noting in some detail:[9]

“One final challenge, which I hope to address in my final month as ASA president, concerns issues of significance, multiplicity, and reproducibility. In 2016, the ASA published a statement that simply reiterated what p-values are and are not. It did not recommend specific approaches, other than ‘good statistical practice … principles of good study design and conduct, a variety of numerical and graphical summaries of data, understanding of the phenomenon under study, interpretation of results in context, complete reporting and proper logical and quantitative understanding of what data summaries mean’.

The guest editors of the March 2019 supplement to The American Statistician went further, writing: ‘The ASA Statement on P-Values and Statistical Significance stopped just short of recommending that declarations of “statistical significance” be abandoned. We take that step here. … [I]t is time to stop using the term “statistically significant” entirely’.

Many of you have written of instances in which authors and journal editors – and even some ASA members – have mistakenly assumed this editorial represented ASA policy. The mistake is understandable: The editorial was coauthored by an official of the ASA. In fact, the ASA does not endorse any article, by any author, in any journal – even an article written by a member of its own staff in a journal the ASA publishes.”

Kafadar’s caveat should quash incorrect assertions about the ASA’s position on statistical significance testing. It is a safe bet, however, that such assertions will appear in trial and appellate briefs.

Statistical reasoning is difficult enough for most people, but the hermeneutics of American Statistical Association publications on statistical significance may require a doctorate of divinity degree. In a cleverly titled post, Professor Deborah Mayo argues that there is no other way to interpret the Wasserstein 2019 editorial except as laying down an ASA prescription. Deborah G. Mayo, “Les stats, c’est moi,” Error Philosophy (Dec. 13, 2019). I accept President Kafadar’s correction at face value, and accept that I, like many other readers, misinterpreted the Wasserstein editorial as having the imprimatur of the ASA. Mayo points out, however, that Kafadar’s correction in a newsletter may be insufficient at this point, and that a stronger disclaimer is required. Officers of the ASA are certainly entitled to their opinions and the opportunity to present them, but disclaimers would bring clarity and transparency to published work of these officials.

Wasserstein’s 2019 editorial goes further to make a claim about how his “step” will ameliorate the replication crisis:

“In this world, where studies with ‘p < 0.05’ and studies with ‘p > 0.05 are not automatically in conflict, researchers will see their results more easily replicated – and, even when not, they will better understand why.”

The editorial here seems to be attempting to define replication failure out of existence. This claim, as stated, is problematic. A sophisticated practitioner may think of the situation in which two studies, one with p = .048, and another with p = 0.052 might be said not to be conflict. In real world litigation, however, advocates will take Wasserstein’s statement about studies not in conflict (despite p-values above and below a threshold, say 5%) to the extremes. We can anticipate claims that two similar studies with p-values above and below 5%, say with one p-value at 0.04, and the other at 0.40, will be described as not in conflict, with the second a replication of the first test. It is hard to see how this possible interpretation of Wasserstein’s editorial, although consistent with its language, will advance sound, replicable science.[10]

[1] Ronald L. Wasserstein & Nicole A. Lazar, “The ASA’s Statement on p-Values: Context, Process, and Purpose,” 70 The Am. Statistician 129 (2016).

[2] “The American Statistical Association’s Statement on and of Significance” (Mar. 17, 2016).

[3] See, e.g., “The Education of Judge Rufe – The Zoloft MDL” (April 9, 2016) (Zoloft litigation); “The ASA’s Statement on Statistical Significance – Buzzing from the Huckabees” (Mar. 19, 2016); “The American Statistical Association Statement on Significance Testing Goes to Court – Part I” (Nov. 13, 2018).

[4] Ronald L. Wasserstein, Allen L. Schirm, and Nicole A. Lazar, “Editorial: Moving to a World Beyond ‘p < 0.05’,” 73 Am. Statistician S1, S2 (2019).

[5] Id. at S2.

[6] See “Has the American Statistical Association Gone Post-Modern?” (Mar. 24, 2019); Deborah G. Mayo, “The 2019 ASA Guide to P-values and Statistical Significance: Don’t Say What You Don’t Mean,” Error Statistics Philosophy (June 17, 2019); B. Haig, “The ASA’s 2019 update on P-values and significance,” Error Statistics Philosophy  (July 12, 2019).

[7] See “Statistical Significance at the New England Journal of Medicine” (July 19, 2019); See also Deborah G. Mayo, “The NEJM Issues New Guidelines on Statistical Reporting: Is the ASA P-Value Project Backfiring?” Error Statistics Philosophy  (July 19, 2019).

[8] See Kafadar, “Statistics & Unintended Consequences,” AmStat News 3,4 (June 2019).

[9] Karen Kafadar, “The Year in Review … And More to Come,” AmStat News 3 (Dec. 2019).

[10]  See also Deborah G. Mayo, “P‐value thresholds: Forfeit at your peril,” 49 Eur. J. Clin. Invest. e13170 (2019).

 

Posted in statistical evidence | Comments Off on American Statistical Association – Consensus versus Personal Opinion

Is the IARC Lost in the Weeds?

November 30th, 2019

A couple of years ago, I met David Zaruk at a Society for Risk Analysis meeting, where we were both presenting. I was aware of David’s blogging and investigative journalism, but meeting him gave me a greater appreciation for the breadth and depth of his work. For those of you who do not know David, he is present in cyberspace as the Risk-Monger who blogs about risk and science communications issues. His blog has featured cutting-edge exposés about the distortions in risk communications perpetuated by the advocacy of non-governmental organizations (NGOs). Previously, I have recorded my objections to the intellectual arrogance of some such organizations that purport to speak on behalf of the public interest, when often they act in cahoots with the lawsuit industry in the manufacturing of tort and environmental litigation.

David’s writing on the lobbying and control of NGOs by plaintiffs’ lawyers from the United States should be required reading for everyone who wants to understand how litigation sausage is made. His series, “SlimeGate” details the interplay among NGO lobbying, lawsuit industry maneuvering, and carcinogen determinations at the International Agency for Research on Cancer (IARC). The IARC, a branch of the World Health Organization, is headquartered in Lyon, France. The IARC convenes “working groups” to review the scientific studies of the carcinogencity of various substances and processes. The IARC working groups produce “monographs” of their reviews, and the IARC publishes these monographs, in print and on-line. The United States is in the top tier of participating countries for funding the IARC.

The IARC was founded in 1965, when observational epidemiology was still very much an emerging science, with expertise concentrated in only a few countries. For its first few decades, the IARC enjoyed a good reputation, and its monographs were considered definitive reviews, especially under its first director, Dr. John Higginson, from 1966 to 1981.[1] By the end of the 20th century, the need for the IARC and its reviews had waned, as the methods of systematic review and meta-analyses had evolved significantly, and had became more widely standardized and practiced.

Understandably, the IARC has been concerned that the members of its working groups should be viewed as disinterested scientists. Unfortunately, this concern has been translated into an asymmetrical standard that excludes anyone with a hint of manufacturing connection, but keeps the door open for those scientists with deep lawsuit industry connections. Speaking on behalf of the plaintiffs’ bar, Michael Papantonio, a plaintiffs’ lawyer who founded Mass Torts Made Perfect, noted that “We [the lawsuit industry] operate just like any other industry.”[2]

David Zaruk has shown how this asymmetry has been exploited mercilessly by the lawsuit industry and its agents in connection with the IARC’s review of glyphosate.[3] The resulting IARC classification of glyphosate has led to a litigation firestorm and an all-out assault on agricultural sustainability and productivity.[4]

The anomaly of the IARC’s glyphosate classification has been noted by scientists as well. Dr. Geoffrey Kabat is a cancer epidemiologist, who has written perceptively on the misunderstandings and distortions of cancer risk assessments in various settings.[5] He has previously written about glyphosate in Forbes and elsewhere, but recently he has written an important essay on glyphosate in Issues in Science and Technology, which is published by the National Academies of Sciences, Engineering, and Medicine and Arizona State University. In his essay, Dr. Kabat details how the IARC’s evaluation of glyphosate is an outlier in the scientific and regulatory world, and is not well supported by the available evidence.[6]

The problems with the IARC are both substantive and procedural.[7] One of the key problems that face IARC evaluations is an incoherent classification scheme. IARC evaluations classify putative human carcinogenic risks into five categories: Group I (known), Group 2A (probably), Group 2B (possibly), Group 3 (unclassifiable), and Group 4 (probably not). Group 4 is virtually an empty set with only one substance, caprolactam ((CH2)5C(O)NH), an organic compound used in the manufacture of nylon.

In the IARC evaluation at issue, glyphosate was placed into Group 2A, which would seem to satisfy the legal system’s requirement that an exposure more likely than not causes the harm in question. Appearances and word usage, however, can be deceiving. Probability is a continuous scale from zero to one. In Bayesian decision making, zero and one are unavailable because if either was our starting point, no amount of evidence could ever change our judgment of the probability of causation. (Cromwell’s Rule) The IARC informs us that its use of “probably” is quite idiosyncratic; the probability that a Group 2A agent causes cancer has “no quantitative” meaning. All the IARC intends is that a Group 2A classification “signifies a greater strength of evidence than possibly carcinogenic.”[8]

In other words, Group 2A classifications are consistent with having posterior probabilities of less than 0.5 (or 50 percent). A working group could judge the probability of a substance or a process to be carcinogenic to humans to be greater than zero, but no more than five or ten percent, and still vote for a 2A classification, in keeping with the IARC Preamble. This low probability threshold for a 2A classification converts the judgment of “probably carcinogenic” into a precautionary prescription, rendered when the most probable assessment is either ignorance or lack of causality. There is thus a practical certainty, close to 100%, that a 2A classification will confuse judges and juries, as well as the scientific community.

In IARC-speak, a 2A “probability” connotes “sufficient evidence” in experimental animals, and “limited evidence” in humans. A substance can receive a 2A classification even when the sufficient evidence of carcinogenicity occurs in one non-human animal specie, even though other animal species fail to show carcinogenicity. A 2A classification can raise the thorny question in court whether a claimant is more like a rat or a mouse.

Similarly, “limited evidence” in humans can be based upon inconsistent observational studies that fail to measure and adjust for known and potential confounding risk factors and systematic biases. The 2A classification requires little substantively or semantically, and many 2A classifications leave juries and judges to determine whether a chemical or medication caused a human being’s cancer, when the basic predicates for Sir Austin Bradford Hill’s factors for causal judgment have not been met.[9]

In courtrooms, IARC 2A classifications should be excluded as legally irrelevant, under Rule 403. Even if a 2A IARC classification were a credible judgment of causation, admitting evidence of the classification would be “substantially outweighed by a danger of … unfair prejudice, confusing the issues, [and] misleading the jury….”[10]

The IARC may be lost in the weeds, but there is no need to fret. A little Round Up™ will help.

[1]  See John Higginson, “The International Agency for Research on Cancer: A Brief History of Its History, Mission, and Program,” 43 Toxicological Sci. 79 (1998).

[2]  Sara Randazzo & Jacob Bunge, “Inside the Mass-Tort Machine That Powers Thousands of Roundup Lawsuits,” Wall St. J. (Nov. 25, 2019).

[3]  David Zaruk, “The Corruption of IARC,” Risk Monger (Aug. 24, 2019); David Zaruk, “Greed, Lies and Glyphosate: The Portier Papers,” Risk Monger (Oct. 13, 2017).

[4]  Ted Williams, “Roundup Hysteria,” Slate Magazine (Oct. 14, 2019).

[5]  See, e.g., Geoffrey Kabat, Hyping Health Risks: Environmental Hazards in Everyday Life and the Science of Epidemiology (2008); Geoffrey Kabat, Getting Risk Right: Understanding the Science of Elusive Health Risks (2016).

[6]  Geoffrey Kabat, “Who’s Afraid of Roundup?” 36 Issues in Science and Technology (Fall 2019).

[7]  See Schachtman, “Infante-lizing the IARC” (May 13, 2018); “The IARC Process is Broken” (May 4, 2016). See also Eric Lasker and John Kalas, “Engaging with International Carcinogen Evaluations,” Law360 (Nov. 14, 2019).

[8]  “IARC Preamble to the IARC Monographs on the Identification of Carcinogenic Hazards to Humans,” at Sec. B.5., p.31 (Jan. 2019); See also “IARC Advisory Group Report on Preamble” (Sept. 2019).

[9]  See Austin Bradford Hill, “The Environment and Disease: Association or Causation?” 58 Proc. Royal Soc’y Med. 295 (1965) (noting that only when “[o]ur observations reveal an association between two variables, perfectly clear-cut and beyond what we would care to attribute to the play of chance,” do we move on to consider the nine articulated factors for determining whether an association is causal.

[10]  Fed. R. Evid. 403.

 

Posted in Causation, Rule 702, statistical evidence | Comments Off on Is the IARC Lost in the Weeds?

Does the California State Bar Discriminate Unlawfully?

November 24th, 2019

Earlier this month, various news outlets announced a finding in a California study that black male attorneys are three times more likely to be disciplined by the State Bar than their white male counterparts.[1] Some of the news accounts treated the study findings as conclusions that the Bar had engaged in race discrimination. One particularly irresponsible website proclaimed that “bar discipline is totally racist.”[2] Indeed, the California State Bar itself apparently plans to hire consulting experts to help it achieve “bias-free decision-making and processes,” to eliminate “unintended bias,” and to consider how, if at all, to weigh prior complaints in the disciplinary procedure.[3]

The California Bar’s report was prepared by a social scientist, George Farkas, of the School of Education at University of California, Irvine. Based upon data from attorneys admitted to the California bar between 1990 and 2008, Professor Farkas reported crude prevalence rates of discipline, probation, disbarment, or resignation, by race.[4] The disbarment/ resignation rate for black male lawyers was 3.9%, whereas the rate for white male lawyers was 1%. Disparities, however, are not unlawful discriminations.

The disbarment/resignation rate for black female lawyers was 0.9%, but no one has suggested that there is implicit bias in favor of black women over both black and white male lawyers. White women were twice as likely as Asian women to resign, or be placed on probation or be disbarred (0.4% versus 0.2%).

The ABA’s coverage sheepishly admitted that “[d]ifferences could be explained by the number of complaints received about an attorney, the number of investigations opened, the percentage of investigations in which a lawyer was not represented by counsel, and previous discipline history.”[5]

Farkas’s report of October 31, 2019, was transmitted to the Bar’s Board of Trustees, on November 14th.[6] As anyone familiar with discrimination law would have expected, Professor Farkas conducted multiple regression analyses that adjusted for the number of previous complaints filed against the errant lawyer, and whether the lawyer was represented by counsel before the Bar. The full analyses showed that these other important variables, not race – not could – but did explain variability in discipline rates:

“Statistically, these variables explained all of the differences in probation and disbarment rates by race/ethnicity. Among all variables included in the final analysis, prior discipline history was found to have the strongest effects [sic] on discipline outcomes, followed by the proportion of investigations in which the attorney under investigation was represented by counsel, and the number of investigations.”[7]

The number of previous complaints against a particular lawyer surely has a role in considering whether a miscreant lawyer should be placed on probation, or subjected to disbarment. And without further refinement of the analysis, and irrespective of race or ethnicity, failure to retain counsel for disciplinary hearings may correlate strongly with futility of any defense.

Curiously, the Farkas report did not take into account the race or ethnicity of the complainants before the Bar’s disciplinary committee. The Farkas report seems reasonable as far as it goes, but the wild conclusions drawn in the media would not pass Rule 702 gatekeeping.

[1]  See, e.g., Emma Cueto, “Black Male Attorneys Disciplined More Often, California Study Finds,” Law360 (Nov. 18, 2019); Debra Cassens Weiss, “New California bar study finds racial disparities in lawyer discipline,” Am. Bar Ass’n J. (Nov. 18, 2019).

[2]  Joe Patrice, “Study Finds That Bar Discipline Is Totally Racist Shocking Absolutely No One: Black male attorneys are more likely to be disciplined than white attorneys,” Above the Law (Nov. 19, 2019).

[3]  Debra Cassens Weiss, “New California bar study finds racial disparities in lawyer discipline,” Am. Bar Ass’n J. (Nov. 18, 2019).

[4]  George Farkas, “Discrepancies by Race and Gender in Attorney Discipline by the State Bar of California: An Empirical Analysis” (Oct. 31, 2019).

[5]  Debra Cassens Weiss, supra at note 3.

[6]  Dag MacLeod (Chief of Mission Advancement & Accountability Division) & Ron Pi (Principal Analyst, Office of Research & Institutional Accountability), Report on Disparities in the Discipline System (Nov. 14, 2019).

[7] Dag MacLeod & Pi, Report on Disparities in the Discipline System at 4 (Nov. 14, 2019) (emphasis added).

Posted in statistical evidence | Comments Off on Does the California State Bar Discriminate Unlawfully?

Everything She Just Said Was Bullshit

September 26th, 2019

At this point, most products liability lawyers have read about the New Jersey verdicts returned earlier this month against Johnson & Johnson in four mesothelioma cases.[1] The Middlesex County jury found that the defendant’s talc and its supposed asbestos impurities were a cause of all four mesothelioma cases, and awarded compensatory damages of $37.3 million, in the cases.[2]

Johnson & Johnson was prejudiced by having to try four cases questionably consolidated together, and then hobbled by having its affirmative defense evidence stricken, and finally crucified when the trial judge instructed the jury at the end of the defense lawyer’s closing argument: “everything she just said was bullshit.”

Judge Ana C. Viscomi, who presided over the trial, struck the entire summation of defense lawyer Diane Sullivan. The action effectively deprived Johnson & Johnson of a defense, as can be seen from the verdicts. Judge Viscomi’s egregious ruling was given without explaining which parts of Sullivan’s closing were objectionable, and without giving Sullivan an opportunity to argue against the sanction.

During the course of Sullivan’s closing argument, Judge Viscomi criticized Sullivan for calling the plaintiffs’ lawyers “sinister,” and suggested that her argument was defaming the legal profession in violation of the Rules of Professional Conduct.[3] Sullivan did use the word “sinister” several times, but in each instance, she referred to the plaintiffs’ arguments, allegations, and innuendo about Johnson & Johnson’s action. Judge Viscomi curiously imputed unprofessional conduct to Sullivan for referring to plaintiffs’ counsel’s “shows and props,” as a suggestion that plaintiffs’ counsel had fabricated evidence.

Striking an entire closing argument is, as far as anyone has determined, unprecedented. Of course, Judge Haller is fondly remembered for having stricken the entirety of Vinny Gambini’s opening statement, but the good judge did allow Vinny’s “thank you” to stand:

Vinny Gambini: “Yeah, everything that guy just said is bullshit… Thank you.”

D.A. Jim Trotter: “Objection. Counsel’s entire opening statement is argument.”

Judge Chamberlain Haller: “Sustained. Counselor’s entire opening statement, with the exception of ‘Thank you’ will be stricken from the record.”

My Cousin Vinny (1992).

In the real world of a New Jersey courtroom, even Ms. Sullivan’s expression of gratitude for the jury’s attention and service succumbed to Judge Viscomi’s unprecedented ruling,[4] as did almost 40 pages of argument in which Sullivan carefully debunked and challenged the opinion testimony of plaintiffs’ highly paid expert witnesses. The trial court’s ruling undermined the defense’s detailed rebuttal of plaintiffs’ evidence, as well as the defense’s comment upon the plaintiffs’ witnesses’ lack of credibility.

Judge Viscomi’s sua sponte ruling appears even more curious given what took place in the aftermath of her instructing the jury to disregard Sullivan’s argument. First, the trial court gave very disparate treatment to plaintiffs’ counsel. The lawyers for the plaintiffs gave extensive closing arguments that were replete with assertions that Johnson & Johnson and Ms. Sullivan were liars, predators, manipulators, poisoners, baby killers, and then some. Sullivan’s objections were perfunctorily overruled. Second, Judge Viscomi permitted plaintiffs’ counsel to comment extensively upon Ms. Sullivan’s closing, even though it had been stricken. Third, despite the judicial admonition about the Rules of Professional Conduct, neither the trial judge nor plaintiffs’ counsel appear to have filed a disciplinary complaint against Ms. Sullivan. Of course, if Judge Viscomi or the plaintiffs’ counsel thought that Ms. Sullivan had violated the Rules, then they would be obligated to report Ms. Sullivan for misconduct.

Bottom line: these verdicts are unsafe.

[1]  The cases were tried in a questionable consolidation in the New Jersey Superior Court, for Middlesex County, before Judge Viscomi. Barden v. Brenntag North America, No. L-1809-17; Etheridge v. Brenntag North America, No. L-932-17; McNeill-George v. Brenntag North America, No. L-7049-16; and Ronning v. Brenntag North America, No. L-6040-17.

[2]  Bill Wichert, “J&J Hit With $37.3M Verdict In NJ Talc Case,” Law360 (Sept. 11, 2019).

[3]  Amanda Bronstad, “J&J Moves for Talc Mistrial After Judge Strikes Entire Closing Argument,” N.J.L.J. (Sept. 10, 2019) (describing Judge Viscomi as having admonished Ms. Sullivan to “[s]top denigrating the lawyers”; J&J’s motion for mistrial was made before the case was submitted to the jury).

[4]  See Peder B. Hong, “Summation at the Border: Serious Misconduct in Final Argument in Civil Trials,” 19 Hamline L. Rev. 179 (1995); Ty Tasker, “Stick and Stones: Judicial Handling of Invective in Advocacy,” 42 Judges J. 17 (2003); Janelle L. Davis, “Sticks and Stones May Break My Bones, But Names Could Get Me a Mistrial: An Examination of Name-Calling in Closing Argument in Civil Cases,” 42 Gonzaga L. Rev. 133 (2011).

Posted in Asbestos, Trial Procedure | Comments Off on Everything She Just Said Was Bullshit

Palavering About P-Values

August 17th, 2019

The American Statistical Association’s most recent confused and confusing communication about statistical significance testing has given rise to great mischief in the world of science and science publishing.[1] Take for instance last week’s opinion piece about “Is It Time to Ban the P Value?” Please.

Helena Chmura Kraemer is an accomplished professor of statistics at Stanford University. This week the Journal of the American Medical Association network flagged Professor Kraemer’s opinion piece on p-values as one of its most read articles. Kraemer’s eye-catching title creates the impression that the p-value is unnecessary and inimical to valid inference.[2]

Remarkably, Kraemer’s article commits the very mistake that the ASA set out to correct back in 2016,[3] by conflating the probability of the data under a hypothesis of no association with the probability of a hypothesis given the data:

“If P value is less than .05, that indicates that the study evidence was good enough to support that hypothesis beyond reasonable doubt, in cases in which the P value .05 reflects the current consensus standard for what is reasonable.”

The ASA tried to break the bad habit of scientists’ interpreting p-values as allowing us to assign posterior probabilities, such as beyond a reasonable doubt, to hypotheses, but obviously to no avail.

Kraemer also ignores the ASA 2016 Statement’s teaching of what the p-value is not and cannot do, by claiming that p-values are determined by non-random error probabilities such as:

“the reliability and sensitivity of the measures used, the quality of the design and analytic procedures, the fidelity to the research protocol, and in general, the quality of the research.”

Kraemer provides errant advice and counsel by insisting that “[a] non-significant result indicates that the study has failed, not that the hypothesis has failed.” If the p-value is the measure of the probability of observing an association at least as large as obtained given an assumed null hypothesis, then of course a large p-value cannot speak to the failure of the hypothesis, but why declare that the study has failed? The study was perhaps indeterminate, but it still yielded information that perhaps can be combined with other data, or help guide future studies.

Perhaps in her most misleading advice, Kraemer asserts that:

“[w]hether P values are banned matters little. All readers (reviewers, patients, clinicians, policy makers, and researchers) can just ignore P values and focus on the quality of research studies and effect sizes to guide decision-making.”

Really? If a high quality study finds an “effect size” of interest, we can now ignore random error?

The ASA 2016 Statement, with its “six principles,” has provoked some deliberate or ill-informed distortions in American judicial proceedings, but Kraemer’s editorial creates idiosyncratic meanings for p-values. Even the 2019 ASA “post-modernism” does not advocate ignoring random error and p-values, as opposed to proscribing dichotomous characterization of results as “statistically significant,” or not.[4] The current author guidelines for articles submitted to the Journals of the American Medical Association clearly reject this new-fangled rejection of evaluating this new-fangled rejection of the need to assess the role of random error.[5]

[1]  See Ronald L. Wasserstein, Allen L. Schirm, and Nicole A. Lazar, “Editorial: Moving to a World Beyond ‘p < 0.05’,” 73 Am. Statistician S1, S2 (2019).

[2]  Helena Chmura Kraemer, “Is It Time to Ban the P Value?” J. Am. Med. Ass’n Psych. (August 7, 2019), in-press at doi:10.1001/jamapsychiatry.2019.1965.

[3]  Ronald L. Wasserstein & Nicole A. Lazar, “The ASA’s Statement on p-Values: Context, Process, and Purpose,” 70 The American Statistician 129 (2016).

[4]  “Has the American Statistical Association Gone Post-Modern?” (May 24, 2019).

[5]  See instructions for authors at https://jamanetwork.com/journals/jama/pages/instructions-for-authors

Posted in statistical evidence, Uncategorized | Comments Off on Palavering About P-Values

Mass Torts Made Less Bad – The Zambelli-Weiner Affair in the Zofran MDL

July 30th, 2019

Judge Saylor, who presides over the Zofran MDL, handed down his opinion on the Zambelli-Weiner affair, on July 25, 2019.[1] As discussed on these pages back in April of this year,[2] GlaxoSmithKline (GSK), the defendant in the Zofran birth defects litigation, sought documents from plaintiffs and Dr Zambelli-Weiner (ZW) about her published study on Zofran and birth defects.[3] Plaintiffs refused to respond to the discovery on grounds of attorney work product,[4] and of consulting expert witness confidential communications.[5] After an abstract of ZW’s study appeared in print, GSK subpoenaed ZW and her co-author, Dr. Russell Kirby, for a deposition and for production of documents.

Plaintiffs’ counsel sought a protective order. Their opposition relied upon a characterization of ZW as a research scientist; they conveniently ommitted their retention of her as a paid expert witness. In December 2018, the MDL court denied plaintiffs’ motion for a protective order, and allowed the deposition to go forward to explore the financial relationship between counsel and ZW.

In January 2019, when GSK served ZW with its subpoena duces tecum, ZW through her own counsel moved for a protective order, supported by ZW’s affidavit with factual assertions to support her claim to be not subject to the deposition. The MDL court quickly denied her motion, and in short order, her lawyer notified the court that ZW’s affidavit contained “factual misrepresentations,” which she refused to correct, and he sought leave to withdraw.

According to the MDL court, the ZW affidavit contained three falsehoods. She claimed not to have been retained by any party when she had been a paid consultant to plaintiffs at times over the previous five years, since December 2014. ZW claimed that she had no factual information about the litigation, when in fact she had participated in a Las Vegas plaintiffs’ lawyers’ conference, “Mass Torts Made Perfect,” in October 2015. Furthermore, ZW falsely claimed that monies received from plaintiffs’ law firms did not go to fund the Zofran study, but went to her company, Translational Technologies International Health Research & Economics, for unrelated work. ZW received in excess of $200,000 for her work on the Zofran study.

After ZW obtained new counsel, she gave deposition testimony in February 2019, when she acknowledged the receipt of money for the study, and the lengthy relationship with plaintiffs’ counsel. Armed with this information, GSK moved for full responses to its document requests. Again, plaintiffs’ counsel and ZW resisted on grounds of confidentiality and privilege.

Judge Saylor reviewed the requested documents in camera, and held last week that they were not protected by consulting expert witness privilege or by attorney work product confidentiality. ZW’s materials and communications in connection with the Las Vegas plaintiffs’ conference never had the protection of privilege or confidentiality. ZW presented at a “quasi-public” conference attended by lawyers who had no connection to the Zofran litigation.[6]

With respect to work product claims, Judge Saylor found that GSK had shown “exceptional circumstances” and “substantial need” for the requested materials given that the plaintiffs’ testifying expert witnesses had relied upon the ZW study, which had been covertly financially supported by plaintiffs’ lawyers.[7] With respect to whatever was thinly claimed to be privileged and confidential, Judge Saylor found the whole arrangement to fail the smell test:[8]

“It is troublesome, to say the least, for a party to engage a consulting, non-testifying expert; pay for that individual to conduct and publish a study, or otherwise affect or influence the study; engage a testifying expert who relies upon the study; and then cloak the details of the arrangement with the consulting expert in the confidentiality protections of Rule 26(b) in order to conceal it from a party opponent and the Court. The Court can see no valid reason to permit such an arrangement to avoid the light of discovery and the adversarial process. Under the circumstances, GSK has made a showing of substantial need and an inability to obtain these documents by other means without undue hardship.

Furthermore, in this case, the consulting expert made false statements to the Court as to the nature of her relationship with plaintiffs’ counsel. The Court would not have been made aware of those falsehoods but for the fact that her attorney became aware of the issue and sought to withdraw. Certainly plaintiffs’ counsel did nothing at the time to correct the false impressions created by the affidavit. At a minimum, the submission of those falsehoods effectively waived whatever protections might otherwise apply. The need to discover the truth and correct the record surely outweighs any countervailing policy in favor of secrecy, particularly where plaintiffs’ testifying experts have relied heavily on Dr. Zambelli-Weiner’s study as a basis for their causation opinions. In order to effectively cross-examine plaintiffs’ experts about those opinions at trial, GSK is entitled to review the documents. At a minimum, the documents shed additional light on the nature of the relationship between Dr. Zambelli-Weiner and plaintiffs’ counsel, and go directly to the credibility of Dr. Zambelli-Weiner and the reliability of her study results.”

It remains to be seen whether Judge Saylor will refer the matter of ZW’s false statements in her affidavit to the U.S. Attorney’s office, or the lawyers’ complicity in perpetuating these falsehoods to disciplinary boards.

Mass torts will never be perfect, or even very good. Judge Saylor, however, has managed to make the Zofran litigation a little less bad.

[1]  Memorandum and order on In Camera Production of Documents Concerning Dr. April Zambelli-Weiner, In re Zofran Prods. Liab. Litig., MDL 2657, D.Mass. (July 25, 2019) [cited as Mem.].

[2]  NAS, “Litigation Science – In re Zambelli-Weiner” (April 8, 2019).

[3]  April Zambelli-Weiner, et al., “First Trimester Ondansetron Exposure and Risk of Structual Birth Defects,” 83 Reproductive Toxicol. 14 (2019).

[4]  Fed. R. Civ. P. 26(b)(3).

[5]  Fed. R. Civ. P. 26(b)(4)(D).

[6]  Mem. at 7-9.

[7]  Mem. at 9.

[8]  Mem. at 9-10.

Posted in Conflicts of Interest, Data Sharing, Expert Witness Discovery, Scientific Misconduct | Comments Off on Mass Torts Made Less Bad – The Zambelli-Weiner Affair in the Zofran MDL

Statistical Significance at the New England Journal of Medicine

July 19th, 2019

Some wild stuff has been going on in the world of statistics, at the American Statistical Association, and elsewhere. A very few obscure journals have declared p-values to be verboten, and presumably confidence intervals as well. The world of biomedical research has generally reacted more sanely, with authors defending the existing frequentist approaches and standards.[1]

This week, the editors of the New England Journal of Medicine have issued new statistical guidelines for authors. The Journal’s approach seems appropriately careful and conservative for the world of biomedical research. In an editorial introducing the new guidelines,[2] the Journal editors remind their potential authors that statistical significance and p-values are here to stay:

“Despite the difficulties they pose, P values continue to have an important role in medical research, and we do not believe that P values and significance tests should be eliminated altogether. A well-designed randomized or observational study will have a primary hypothesis and a prespecified method of analysis, and the significance level from that analysis is a reliable indicator of the extent to which the observed data contradict a null hypothesis of no association between an intervention or an exposure and a response. Clinicians and regulatory agencies must make decisions about which treatment to use or to allow to be marketed, and P values interpreted by reliably calculated thresholds subjected to appropriate adjustments have a role in those decisions.”[3]

The Journal’s editors described their revamped statistical policy as being based upon three premises:

(1) adhering to prespecified analysis plans if they exist;

(2) declaring associations or effects only for statistical analyses that have pre-specified “a method for controlling type I error”; and

(3) presenting evidence about clinical benefits or harms requires “both point estimates and their margins of error.”

With a hat tip to the ASA’s recent pronouncements on statistical significance,[4] the editors suggest that their new guidelines have moved away from bright-line applications of statistical significance “as a bright-line marker for a conclusion or a claim”[5]:

“[T]he notion that a treatment is effective for a particular outcome if P < 0.05 and ineffective if that threshold is not reached is a reductionist view of medicine that does not always reflect reality.”[6]

The editors’ language intimates greater latitude for authors in claiming associations or effects from their studies, but this latitude may well be circumscribed by tighter control over such claims in the inevitable context of multiple testing within a dataset.

The editors’ introduction of the new guidelines is not entirely coherent. The introductory editorial notes that the use of p-values for reporting multiple outcomes, without adjustments for multiplicity, inflates the number of findings with p-values less than 5%. The editors thus caution against “uncritical interpretation of multiple inferences,” which can be particularly threatening to valid inference when not all the comparisons conducted by the study investigators have been reported in their manuscript.[7] They reassuringly tell prospective authors that many methods are available to adjust for multiple comparisons, and can be used to control Type I error probability “when specified in the design of a study.”[8]

But what happens when such adjustment methods are not pre-specified in the study design? Failure to to do so do not appear to be disqualifying factors for publication in the Journal. For one thing, when the statistical analysis plan of the study has not specified adjustment methods for controlling type I error probabilities, then authors must replace p-values with “estimates of effects or association and 95% confidence intervals.”[9] It is hard to understand how this edict helps when the specified coefficient of 95% is a continuation of the 5% alpha, which would have been used in any event. The editors seem to be saying that if authors fail to pre-specify or even post-specify methods for controlling error probabilities, then they cannot declare statistical significance, or use p-values, but they can use confidence intervals in the same way they have been using them, and with the same misleading interpretations supplied by their readers.

More important, another price authors will have to pay for multiple testing without pre-specified methods of adjustment is that they will affirmatively have to announce their failure to adjust for multiplicity and that their putative associations “may not be reproducible.” Tepid as this concession is, it is better than previous practice, and perhaps it will become a badge of shame. The crucial question is whether judges, in exercising their gatekeeping responsibilities, will see these acknowledgements as disabling valid inferences from studies that carry this mandatory warning label.

The editors have not issued guidelines for the use of Bayesian statistical analyses, because “the large majority” of author manuscripts use only frequentist analyses.[10] The editors inform us that “[w]hen appropriate,” they will expand their guidelines to address Bayesian and other designs. Perhaps this expansion will be appropriate when Bayesian analysts establish a track record of abuse in their claiming of associations and effects.

The new guidelines themselves are not easy to find. The Journal has not published these guidelines as an article in their published issues, but has relegated them to a subsection of their website’s instructions to authors for new manuscripts:

https://www.nejm.org/author-center/new-manuscripts

Presumably, the actual author instructions control in any perceived discrepancy between this week’s editorial and the guidelines themselves. Authors are told that p-values generally should be two-sided. Authors’ use of:

“Significance tests should be accompanied by confidence intervals for estimated effect sizes, measures of association, or other parameters of interest. The confidence intervals should be adjusted to match any adjustment made to significance levels in the corresponding test.”

Similarly, the guidelines call for, but do not require, pre-specified methods of controlling family-wide error rates for multiple comparisons. For observational studies submitted without pre-specified methods of error control, the guidelines recommend the use of point estimates and 95% confidence intervals, with an explanation that the interval widths have not been adjusted for multiplicity, and a caveat that the inferences from these findings may not be reproducible. The guidelines recommend against using p-values for such results, but again, it is difficult to see why reporting the 95% confidence intervals is recommended when p-values are not recommended.

[1]  Jonathan A. Cook, Dean A. Fergusson, Ian Ford, Mithat Gonen, Jonathan Kimmelman, Edward L. Korn, and Colin B. Begg, “There is still a place for significance testing in clinical trials,” 16 Clin. Trials 223 (2019).

[2]  David Harrington, Ralph B. D’Agostino, Sr., Constantine Gatsonis, Joseph W. Hogan, David J. Hunter, Sharon-Lise T. Normand, Jeffrey M. Drazen, and Mary Beth Hamel, “New Guidelines for Statistical Reporting in the Journal,” 381 New Engl. J. Med. 285 (2019).

[3]  Id. at 286.

[4]  See id. (“Journal editors and statistical consultants have become increasingly concerned about the overuse and misinterpretation of significance testing and P values in the medical literature. Along with their strengths, P values are subject to inherent weaknesses, as summarized in recent publications from the American Statistical Association.”) (citing Ronald L. Wasserstein & Nicole A. Lazar, “The ASA’s statement on p-values: context, process, and purpose,” 70 Am. Stat. 129 (2016); Ronald L. Wasserstein, Allen L. Schirm, and Nicole A. Lazar, “Moving to a world beyond ‘p < 0.05’,” 73 Am. Stat. s1 (2019)).

[5]  Id. at 285.

[6]  Id. at 285-86.

[7]  Id. at 285.

[8]  Id., citing Alex Dmitrienko, Frank Bretz, Ajit C. Tamhane, Multiple testing problems in pharmaceutical statistics (2009); Alex Dmitrienko & Ralph B. D’Agostino, Sr., “Multiplicity considerations in clinical trials,” 378 New Engl. J. Med. 2115 (2018).

[9]  Id.

[10]  Id. at 286.

Posted in Scientific Evidence, statistical evidence | Comments Off on Statistical Significance at the New England Journal of Medicine

Science Bench Book for Judges

July 13th, 2019

On July 1st of this year, the National Judicial College and the Justice Speakers Institute, LLC released an online publication of the Science Bench Book for Judges [Bench Book]. The Bench Book sets out to cover much of the substantive material already covered by the Federal Judicial Center’s Reference Manual:

Acknowledgments

Table of Contents

  1. Introduction: Why This Bench Book?
  2. What is Science?
  3. Scientific Evidence
  4. Introduction to Research Terminology and Concepts
  5. Pre-Trial Civil
  6. Pre-trial Criminal
  7. Trial
  8. Juvenile Court
  9. The Expert Witness
  10. Evidence-Based Sentencing
  11. Post Sentencing Supervision
  12. Civil Post Trial Proceedings
  13. Conclusion: Judges—The Gatekeepers of Scientific Evidence

Appendix 1 – Frye/Daubert—State-by-State

Appendix 2 – Sample Orders for Criminal Discovery

Appendix 3 – Biographies

The Bench Book gives some good advice in very general terms about the need to consider study validity,[1] and to approach scientific evidence with care and “healthy skepticism.”[2] When the Bench Book attempts to instruct on what it represents the scientific method of hypothesis testing, the good advice unravels:

“A scientific hypothesis simply cannot be proved. Statisticians attempt to solve this dilemma by adopting an alternate [sic] hypothesis – the null hypothesis. The null hypothesis is the opposite of the scientific hypothesis. It assumes that the scientific hypothesis is not true. The researcher conducts a statistical analysis of the study data to see if the null hypothesis can be rejected. If the null hypothesis is found to be untrue, the data support the scientific hypothesis as true.”[3]

Even in experimental settings, a statistical analysis of the data do not lead to a conclusion that the null hypothesis is untrue, as opposed to not reasonably compatible with the study’s data. In observational studies, the statistical analysis must acknowledge whether and to what extent the study has excluded bias and confounding. When the Bench Book turns to speak of statistical significance, more trouble ensues:

“The goal of an experiment, or observational study, is to achieve results that are statistically significant; that is, not occurring by chance.”[4]

In the world of result-oriented science, and scientific advocacy, it is perhaps true that scientists seek to achieve statistically significant results. Still, it seems crass to come right out and say so, as opposed to saying that the scientists are querying the data to see whether they are compatible with the null hypothesis. This first pass at statistical significance is only mildly astray compared with the Bench Book’s more serious attempts to define statistical significance and confidence intervals:

“4.10 Statistical Significance

The research field agrees that study outcomes must demonstrate they are not the result of random chance. Leaving room for an error of .05, the study must achieve a 95% level of confidence that the results were the product of the study. This is denoted as p ≤ 05. (or .01 or .1).”[5]

and

“The confidence interval is also a way to gauge the reliability of an estimate. The confidence interval predicts the parameters within which a sample value will fall. It looks at the distance from the mean a value will fall, and is measured by using standard deviations. For example, if all values fall within 2 standard deviations from the mean, about 95% of the values will be within that range.”[6]

Of course, the interval speaks to the precision of the estimate, not its reliability, but that is a small point. These definitions are virtually guaranteed to confuse judges into conflating statistical significance and the coefficient of confidence with the legal burden of proof probability.

The Bench Book runs into problems in interpreting legal decisions, which would seem softer grist for the judicial mill. The authors present dictum from the Daubert decision as though it were a holding:[7]

“As noted in Daubert, ‘[t]he focus, of course, must be solely on principles and methodology, not on the conclusions they generate’.”

The authors fail to mention that this dictum was abandoned in Joiner, and that it is specifically rejected by statute, in the 2000 revision to the Federal Rule of Evidence 702.

Early in the Bench Book, it authors present a subsection entitled “The Myth of Scientific Objectivity,” which they might have borrowed from Feyerabend or Derrida. The heading appears misleading because the text contradicts it:

“Scientists often develop emotional attachments to their work—it can be difficult to abandon an idea. Regardless of bias, the strongest intellectual argument, based on accepted scientific hypotheses, will always prevail, but the road to that conclusion may be fraught with scholarly cul-de-sacs.”[8]

In a similar vein, the authors misleadingly tell readers that “the forefront of science is rarely encountered in court,” and so “much of the science mentioned there shall be considered established….”[9] Of course, the reality is that many causal claims presented in court have already been rejected or held to be indeterminate by the scientific community. And just when readers may think themselves safe from the goblins of nihilism, the authors launch into a theory of naïve probabilism that science is just placing subjective probabilities upon data, based upon preconceived biases and beliefs:

“All of these biases and beliefs play into the process of weighing data, a critical aspect of science. Placing weight on a result is the process of assigning a probability to an outcome. Everything in the universe can be expressed in probabilities.”[10]

So help the expert witness who honestly (and correctly) testifies that the causal claim or its rejection cannot be expressed as a probability statement!

Although I have not read all of the Bench Book closely, there appears to be no meaningful discussion of Rule 703, or of the need to access underlying data to ensure that the proffered scientific opinion under scrutiny has used appropriate methodologies at every step in its development. Even a 412 text cannot address every issue, but this one does little to help the judicial reader find more in-depth help on statistical and scientific methodological issues that arise in occupational and environmental disease claims, and in pharmaceutical products litigation.

The organizations involved in this Bench Book appear to be honest brokers of remedial education for judges. The writing of this Bench Book was funded by the State Justice Institute (SJI) Which is a creation of federal legislation enacted with the laudatory goal of improving the quality of judging in state courts.[11] Despite its provenance in federal legislation, the SJI is a a private, nonprofit corporation, governed by 11 directors appointed by the President, and confirmed by the Senate. A majority of the directors (six) are state court judges, one state court administrator, and four members of the public (no more than two from any one political party). The function of the SJI is to award grants to improve judging in state courts.

The National Judicial College (NJC) originated in the early 1960s, from the efforts of the American Bar Association, American Judicature Society and the Institute of Judicial Administration, to provide education for judges. In 1977, the NJC became a Nevada not-for-profit (501)(c)(3) educational corporation, which its campus at the University of Nevada, Reno, where judges could go for training and recreational activities.

The Justice Speakers Institute appears to be a for-profit company that provides educational resources for judge. A Press Release touts the Bench Book and follow-on webinars. Caveat emptor.

The rationale for this Bench Book is open to question. Unlike the Reference Manual for Scientific Evidence, which was co-produced by the Federal Judicial Center and the National Academies of Science, the Bench Book’s authors are lawyers and judges, without any subject-matter expertise. Unlike the Reference Manual, the Bench Book’s chapters have no scientist or statistician authors, and it shows. Remarkably, the Bench Book does not appear to cite to the Reference Manual or the Manual on Complex Litigation, at any point in its discussion of the federal law of expert witnesses or of scientific or statistical method. Perhaps taxpayers would have been spared substantial expense if state judges were simply encouraged to read the Reference Manual.

[1]  Bench Book at 190.

[2]  Bench Book at 174 (“Given the large amount of statistical information contained in expert reports, as well as in the daily lives of the general society, the ability to be a competent consumer of scientific reports is challenging. Effective critical review of scientific information requires vigilance, and some healthy skepticism.”).

[3]  Bench Book at 137; see also id. at 162.

[4]  Bench Book at 148.

[5]  Bench Book at 160.

[6]  Bench Book at 152.

[7]  Bench Book at 233, quoting Daubert v. Merrell Dow Pharms., Inc., 509 U.S. 579, 595 (1993).

[8]  Bench Book at 10.

[9]  Id. at 10.

[10]  Id. at 10.

[11] See State Justice Institute Act of 1984 (42 U.S.C. ch. 113, 42 U.S.C. § 10701 et seq.).

Posted in Causation, Evidence, Expert Witness Discovery, Expert Witnesses, Frye, Reference Manual on Scientific Evidence, Rule 702, Rule 703, Scientific Evidence, statistical evidence | Comments Off on Science Bench Book for Judges

« Older Entries
Newer Entries »

The opinions, statements, and asseverations expressed on Tortini are my own, or those of invited guests, and these writings do not necessarily represent the views of clients, friends, or family, even when supported by good and sufficient reason.