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

Probabilism Case Law

January 28th, 2013

Some judges and commentators have characterized all evidence as ultimately “probable,” but other writers have criticized this view as trading on the ambiguities inherent in our ordinary usage of probable to convey an epistemic hedge or uncertainty.  How successful is the probabilistic program in the law?  In the context of assessing causation, many courts have succumbed to the temptation to substitute risk for causation.  Other courts have noticed the difference between a prospective risk and a retrospective factual determination that a risk factor actually participated in bringing about the caused result.  In any event, judicial skepticism about probabilistic evidence, in many contexts, has found its expression in holdings and in dicta of common law courts.  The following is a chronological listing of some pertinent cases that rejected or limited the use of overtly probabilistic evidence. There are only two cases involving epidemiological evidence before 1970 on the list.

Day v. Boston & Maine R.R., 96 Me. 207, 217–218, 52 A. 771, 774 (1902) (“Quantitative probability, however, is only the greater chance. It is not proof, nor even probative evidence, of the proposition to be proved. That in one throw of dice, there is a quantitative probability, or greater chance, that a less number of spots than sixes will fall uppermost is no evidence whatever that in a given throw such was the actual result. Without something more, the actual result of the throw would still be utterly unknown. The slightest real evidence would outweigh all the probability otherwise.”)

Toledo, St. L. & W. R. Co. v. Howe, 191 F. 776, 782-83 (6th Cir. 1911) (holding that evidence at issue was not probabilistic, but noting in dictum that “[n]o man’s property should be taken from him on the mere guess that he has committed a wrong. . . because of a probability among other probabilities that the accident for which recovery is sought might have happened in the way charged.”)

People v. Risley, 214 N.Y. 75, 86, 108 N.E. 200, 203 (1915) (holding that probability calculations were improper when “the fact to be established in this case was not the probability of a future event, but whether an occurrence asserted by the people to have happened had actually taken place”)

Lampe v. Franklin Am. Trust, 339 Mo. 361, 384, 96 S.W.2d 710, 723 (1936) (verdict must be based upon what the jury finds to be facts rather than what they find to be ‘more probable’.)

Sargent v. Massachusetts Accident Co., 307 Mass. 246, 250, 29 N.E.2d 825, 827 (1940) (the preponderance standard requires more than showing that the chances mathematically favor a fact in dispute; the proponent must prove the proposition in dispute such that the jurors form an actual belief in the truth of the proposition) (“It has been held not enough that mathematically the chances somewhat favor a proposition to be proved; for example, the fact that colored automobiles made in the current year outnumber black ones would not warrant a finding that an undescribed automobile of the current year is colored and not black, nor would the fact that only a minority of men die of cancer warrant a finding that a particular man did not die of cancer. The weight or preponderance of the evidence is its power to convince the tribunal which has the determination of the fact, of the actual truth of the proposition to be proved. After the evidence has been weighed, that proposition is proved by a preponderance of the evidence if it is made to appear more likely or probable in the sense that actual belief in its truth, derived from the evidence, exists in the mind or minds of the tribunal notwithstanding any doubts that may linger there.”)

Smith v. Rapid Transit, 317 Mass. 469, 470, 58 N.E.2d 754, 755 (1945) (evidence that defendant was the only bus franchise operating in the area where the accident took place was not sufficient to establish that the bus that caused the accident belonged to the defendant where private or chartered buses could have been in the area; it is not enough that mathematically the chances somewhat favor the proposition to be proved)

Kamosky v Owens-Illinois Co., 89 F. Supp. 561, 561-62 (M.D.Pa. 1950) (directing verdict in favor of defendant; statistical likelihood that defendant manufactured the bottle that injured plaintiff was insufficient to satisfy plaintiff’s burden of proof)

Mahoney v. United States, 220 F. Supp. 823, 840 41 (E.D. Tenn. 1963) (Taylor, C.J.) (holding that plaintiffs had failed to prove that their cancers were caused by radiation exposures, on the basis of their statistical, epidemiological proofs), aff’d, 339 F.2d 605 (6th Cir. 1964) (per curiam)

In re King, 352 Mass. 488, 491-92, 225 N.E.2d 900, 902 (1967) (physician expert’s opinion that expressed a mathematical likelihood, unsupported by clinical evidence, that claimant’s death from cancer was caused by his accidental fall was legally insufficient to support a judgment)

Garner v. Heckla Mining Co., 19 Utah 2d 367, 431 P.2d 794, 796 97 (1967) (affirming denial of compensation to family of a uranium miner who had smoked cigarettes and had died of lung cancer; statistical evidence of synergistically increased risk of lung cancer among uranium miners is insufficient to show causation of decedent’s lung cancer, especially considering his having smoked cigarettes)

Whitehurst v. Revlon, 307 F. Supp. 918, 920 (E.D. Va. 1969) (holding that challenged evidence was not probabilistic, and noting in dictum that probability evidence of negligence evidence would leave verdict based upon conjecture, guess or speculation)

Guenther v. Armstrong Rubber Co., 406 F.2d 1315, 1318 (3d Cir. 1969) (holding that defendant cannot be found liable on the basis that it supplied 75-80% of the kind of tire purchased by the plaintiff; any verdict based on this evidence “would at best be a guess”)

Crawford v. Industrial Comm’n, 23 Ariz. App. 578, 582-83, 534 P.2d 1077, 1078, 1082-83 (1975) (affirming an employee’s award of no compensation because he was exposed to disease producing conditions both on and off the job; a physician’s testimony, expressed to a reasonable degree of medical certainty that the working conditions statistically increased the probability of developing a disease does not satisfy the reasonable certainty standard)

Olson v. Federal American Partners, 567 P.2d 710, 712 13 (Wyo. 1977) (affirming judgment for employer in compensation proceedings; cigarette smoking claimant failed to show that his lung cancer resulted from workplace exposure to radiation, despite alleged synergism between smoking and radiation).

Heckman v. Federal Press Co., 587 F.2d 612, 617 (3d Cir. 1977) (statistical data about a group do not establish facts about an individual)

Bazemore v. Davis, 394 A.2d 1377, 1382 n.7 (D.C. 1978) (if verdicts were determined on the basis of statistics indicating high probability of alleged facts, more often than not they would be correct guesses, but this is not a sufficient basis for reaching verdicts)

Kaminsky v. Hertz Corp., 94 Mich. App. 356 (1979) (dictum; reversing summary judgment)

Sulesky v. United States, 545 F. Supp. 426, 430 (S.D.W.Va. 1982) (swine flu vaccine GBS cases; epidemiological studies alone do not prove or disprove causation in an individual)

Robinson v. United States, 533 F. Supp. 320, 330 (E.D. Mich. 1982) (finding for government in swine flu vaccine case; the court found that that the epidemiological evidence offered by the plaintiff was not probative, and that it “would reach the same result if the epidemiological data were entirely excluded since statistical evidence cannot establish cause and effect in an individual”)

Iglarsh v. United States, No. 79 C 2148, 1983 U.S. Dist. LEXIS 10950, *10 (N.D.Ill. Dec. 9, 1983) (“In the absence of a statistically valid epidemiological study, even the plaintiff’s treating physician or expert witness, or any clinician for that matter, is unable to attribute a plaintiff’s injury to the swine flu vaccination.”)

Johnston v. United States, 597 F. Supp. 374, 412, 425-26 (D.Kan. 1984) (although the probability of attribution increases with the relative risk, expert must still speculate in making an individual attribution; “a statistical method which shows a greater than 50% probability does not rise to the required level of proof; plaintiffs’ expert witnesses’ reports were “statistical sophistry,” not medical opinion)

Kramer v. Weedhopper of Utah, Inc., 490 N.E.2d 104, 108 (Ill. App. Ct. 1986) (Stamos, J., dissenting) (“Liability is not based on a balancing of probabilities, but on a finding of fact.  While the majority contends that the measure of what is considered sufficient evidence [to support submitting a case to the jury] resolves itself into a question of probability, a review of case law … reveals that a theoretical probability alone cannot be the basis for [a prima facie case].  There must be some evidence in addition to the abstraction which will enable a jury to choose between competing probabilities.”)

Washington v. Armstrong World Industries, 839 F.2d 1121 (5th Cir. 1988) (affirming grant of summary judgment on grounds that statistical correlation between asbestos exposure and disease did not support specific causation)

Thompson v. Merrell Dow Pharm., 229 N.J. Super. 230, 244, 551 A.2d 177, 185 (1988) (epidemiology looks at increased incidences of diseases in populations)

Norman v. National Gypsum Co., 739 F. Supp. 1137, 1138 (E.D. Tenn. 1990) (statistical evidence of risk of lung cancer from asbestos and smoking was insufficient to show individual causation, without evidence of asbestos fibers in the plaintiff’s lung tissue)

Smith v. Ortho Pharmaceutical Corp., 770 F. Supp. 1561, 1576 (N.D. Ga. 1991) (“The court notes that, in an individual case, epidemiology cannot conclusively prove causation; at best, it can establish only a certain probability that a randomly selected case of birth defect was one that would not have occurred absent exposure (or the ‘relative risk’ of the exposed population).”)

Smith v. Ortho Pharmaceutical Corp., 770 F. Supp. 1561, 1573 (N.D. Ga. 1991) (“However, in an individual case, epidemiology cannot conclusively prove causation; at best, it can only establish a certain probability that a randomly selected case of disease was one that would not have occurred absent exposure, or the ‘relative risk’ of the exposed population.  Epidemiology, therefore, involves evidence on causation derived from group-based information, rather than specific conclusions regarding causation in an individual case.”)

Howard v. Wal-Mart Stores, Inc., 160 F.3d 358, 359–60 (7th Cir. 1998) (Posner, C.J.)

Krim v., Inc., 402 F.3d 489 (5th Cir. 2005) (rejecting standing plaintiffs’ standing to sue for fraud absent a showing of actual tracing of shares to the offending public offering; statistical likelihood of those shares having been among those purchased was insufficient to confer standing)

New Release of PLI’s Treatise on Product Liability Litigation

January 19th, 2013

The Practicing Law Institute (PLI) has released a new edition of its treatise on product liability litigation.  Stephanie A. Scharf, Lise T. Spacapan, Traci M. Braun, and Sarah R. Marmor, eds., Product Liability Litigation:  Current Law, Strategies and Best Practices (PLI Dec. 2012).

The new edition, the third release of the treatise, has several new chapters, including my contribution, Chapter 30A, “Statistical Evidence in Products Liability Litigation,” which discusses the use of, and recent developments, in statistical and scientific evidence in the law, including judicial mishandling of “significance probability,” statistical significance, statistical power, and meta-analysis.  Here is the table of contents for this new chapter on statistical evidence:

  • § 30A:1 : Overview 30A-2
  • § 30A:2 : Litigation Context of Statistical Issues 30A-2
  • § 30A:3 : Qualification of Expert Witnesses Who Give Testimony on Statistical Issues 30A-3
  • § 30A:4 : Admissibility of Statistical Evidence—Rules 702 and 703 30A-3
  • § 30A:5 : Significance Probability 30A-5
    • § 30A:5.1 : Definition of Significance Probability (The “p-value”) 30A-5
    • § 30A:5.2 : The Transpositional Fallacy 30A-5
    • § 30A:5.3 : Confusion Between Significance Probability and The Burden of Proof 30A-6
    • § 30A:5.4 : Hypothesis Testing 30A-7
    • § 30A:5.5 : Confidence Intervals 30A-8
    • § 30A:5.6 : Inappropriate Use of Statistical Significance—Matrixx Initiatives, Inc. v. Siracusano 30A-9
      • [A] : Sequelae of Matrixx Initiatives 30A-12
      • [B] : Is Statistical Significance Necessary? 30A-13
  • § 30A:6 : Statistical Power30A-14
    • § 30A:6.1 : Definition of Statistical Power 30A-14
    • § 30A:6.2 : Cases Involving Statistical Power 30A-15
  • § 30A:7 : Meta-Analysis 30A-17
    • § 30A:7.1 : Definition and History of Meta-Analysis 30A-17
    • § 30A:7.2 : Consensus Statements 30A-18
    • § 30A:7.3 : Use of Meta-Analysis in Litigation 30A-18
    • § 30A:7.4 : Competing Models for Meta-Analysis 30A-20
    • § 30A:7.5 : Recent Cases Involving Meta-Analyses 30A-21
  • § 30A:8 : Conclusion 30A-23

The treatise weighs in with over 40 chapters, and over 1,000 pages.  The table of contents and table of authorities are available online at the PLI’s website.

The PLI is a non-profit educational organization, chartered by the Regents of the University of the State of New York.  The PLI provides continuing legal education, and publishes treatises and handbooks geared for the practitioner.

Egilman Instigates Kerfuffle at McGill University

January 15th, 2013

Last February, the Canadian Broadcast Corporation unleashed a one-sided, twenty minute investigative journalistic film on the Quebec asbestos industry.  All allegations from the plaintiffs’ litigation world were accepted as true, and the asbestos mining industry was cast as a manufacturer of doubt and deception.  See Fatal Deception(Feb 2, 2012). 

The narrator raises the suggestion that the Canadian federal government is relying upon “junk science” to justify support for continuing exports of chrysotile and for reopening the Quebec mines.  This CBC production features Dr. David Egilman, holding forth on his views on the relationship between McGill University, Professor Corbett Macdonald, and the Quebec asbestos industry. Mostly, Egilman is permitted to define the issues and provide the “answers,” although the CBC film does give some air time to Professor Bruce Case, who points out that Egilman is not a scientist, but rather a social critic. When Professor Case was asked on air how he would respond to Egilman in response to his allegations, Case responded, “I wouldn’t give Dr. Egilman the time of day…because he’s not an honorable person.”

For over a decade, Egilman has been pressing his allegations that asbestos research conducted by McGill University investigators was tainted.  In September 2012, McGill University’s Research Integrity Officer, Abraham Fuks, reported that the Egilman allegations were baseless and unsupported.  Consultation Report to Dean David Eidelman (Sept. 23, 2012). See Egilman’s Allegations Against McDonald and His Epidemiologic Research Are Baseless (Oct. 20, 2012).  Egilman responded to Professor Fuks’ report by labeling it “a shameful cover-up.”  Eric Andrew-Gee, “Asbestos debate rages on at the Faculty Club:  American researcher attacks McGill’s asbestos investigation,” The McGill Daily (Jan. 10, 2013).

The Egilman show apparently kicked off the new year at the McGill University Faculty Club, earlier this month, with a shouting match.  According to the University’s newspaper, Egilman called MacDonald’s research on the Quebec chrysotile miners and millers “garbage,” and he called upon McGill University to retract the paper.

Egilman’s argument took the high road and the low road:  He understandably objected to McGill’s and MacDonald’s refusal to share mineralogical data about tremolite content of asbestos from the Thetford Mines.  Of course, the sad state of epidemiology today is that there is no mechanism for requiring data sharing, and the authors of pro-plaintiff studies have consistently refused to share data, and have fought subpoenas tooth and nail.

But then there was the low road. According to the McGill Daily, Egilman lapsed into name calling.  During his presentation, Egilman referred to McGill’s Professor Fuks as Inspector Fox and included a cartoon in his slideshow of a henhouse guarded by a grinning fox.  “Fuks, by the way, is German for Fox,” Egilman said.

One of the McGill professors chided Egilman for his ad hominem attack on Professor Fuks, and pointed out that Egilman could have made his points without personal attacks. Egilman responded “I could have, but it’s funny.” Id.

Egilman called upon his audience to evaluate his claims against those of Professors Case and Fuks. “One of us is an asshole,” he announced. Id. Indeed. Just perform the iterative disjunctive syllogism; it’s a matter of elimination.  For a more scholarly analysis of assholes, see Aaron James, Assholes:  A Theory (2012).

Tunnel Vision on Conflicts of Interest

January 13th, 2013

Judge Alsup’s order requiring disclosure of money paid to bloggers and journalists is only a recent manifestation of a misguided attempt to control conflicts of interest among non-parties.  See Can a Court Engage in Abusive Discovery? (Jan. 10, 2013).  Judge Alsup’s curious orders can be traced to encouragement in the Federal Judicial Center’s “pocket guide” to managing an MDL for products liability cases.   Barbara Rothstein & Catherine  Borden, Managing Multidistrict Litigation in Products Liability Cases: A Pocket Guide for Transferee Judges (2011).  Link or download  This FJC publication suggested that an MDL court should unleash discovery against authors of published works for evidence of bias, citing an MDL trial court that ordered parties to produce lists of payments to authors of articles relied upon by expert witnesses. Id. at 35 n.48 (citing In re Welding Fume Prods. Liab. Litig., 534 F. Supp. 2d 761 (N.D. Ohio 2008).

The United States Supreme Court has also encouraged hostility to party-funded research and writing.  In Exxon Shipping Co. v. Baker, 554 U.S. 471, 501 (2008), the Court struck down a large punitive damage award.  Justice Souter, writing for a divided court, noted in footnote 17:

“The Court is aware of a body of literature running parallel to anecdotal reports, examining the predictability of punitive awards by conducting numerous ‘mock juries’, where different ‘jurors’ are confronted with the same hypothetical case. See, e.g., C. Sunstein, R. Hastie, J. Payne, D. Schkade, W. Viscusi, Punitive Damages: How Juries Decide (2002); Schkade, Sunstein, & Kahneman, Deliberating About Dollars: The Severity Shift, 100 Colum. L.Rev. 1139 (2000); Hastie, Schkade, & Payne, Juror Judgments in Civil Cases: Effects of Plaintiff’s Requests and Plaintiff’s Identity on Punitive Damage Awards, 23 Law & Hum. Behav. 445 (1999); Sunstein, Kahneman, & Schkade, Assessing Punitive Damages (with Notes on Cognition and Valuation in Law), 107 Yale L.J. 2071 (1998). Because this research was funded in part by Exxon, we decline to rely on it.”

Id. at n.17; see also Conflicts of Interest, Footnote 17, and Scientific McCarthyism.  The glib dismissal of behavioral research on a relevant topic by the Supreme Court was remarkable.  Professor Sunstein, is a professor at University of Chicago, and formerly served the Administrator of the White House Office of Information and Regulatory Affairs, in President Obama’s administration.  Professor Kahneman, a Nobel Laureate, is Professor Emeritus in Princeton University. Professor W. Kip Viscusi has been one of the most prolific writers about and investigators of punitive damages.  Justice Souter’s footnote might be interpreted to impugn the integrity of their research by virtue of their corporate sponsorship. More important, Justice Souter’s opinion fails to explain why the Court would not look beyond funding to the merits of the funded research. Courts consider arguments of the parties’ counsel, although of course, the parties compensate their counsel for marshalling facts, and formulating and presenting arguments. Perhaps Justice Souter would have been justified in announcing that he and his judicial colleagues had looked at Sunstein’s research more closely than other cited research.  The wholesale dismissal of relevant evidence based upon funding is irrational.

A new article posted on the Social Science Research Network explores the misdirection and distortion created by the single-minded focus on financial conflicts of interest.  Richard S. Saver,  “Is It Really All About The Money? Reconsidering Non-Financial Interests In Medical Research,” Journal of Law, Medicine & Ethics (forthcoming 2013).

Richard Saver is a professor of law at the University of North Carolina School of Law, and also holds appointments in the UNC’s School of Medicine.  Saver describes how conflicts of interest (COIs) have largely and incorrectly been reduced to financial conflicts.  For instance, in 2011, the National Institutes of Health (NIH) addressed only financial issues when it promulgated rules for managing conflicts of interest in the field of medical research.  Department of Health and Human Services, “Responsibility of Applicants for Promoting Objectivity in Research for Which Public Health Service Funding is Sought and Responsible Prospective Contractors,” 76 Fed. Reg. 53256 (Aug. 25, 2011).  Several commentators advocated regulation of non-financial COI, but the agency refused to include such COIs within its rules. Id. at 53258.  The Institute of Medicine (IOM), in its monograph on COI in medicine, similarly gave almost exclusive priority to financial ties.   Institute of Medicine, Conflict of Interest in Medical Research, Education, and Practice (Washington, D.C.: The National Academies Press, 2009).

Saver argues that the focus on economic COI is dangerous because it instills complacency about non-financial interests, and provides a false sense of assurance that the most serious biases are disclosed or eliminated.  Saver’s review of retractions, frauds, and ethical lapses in biomedical research suggests that non-financial interests, such as friendships and alliances, institutional hierarchies, intellectual biases and commitments, beneficence, “white-hat” advocacy, as well as the drive for professional achievement, recognition, and rewards, all have the potential to complicate, distort, and sometimes undermine scientific research in myriad ways. The failure to recognize serious non-economic COIs and biases, and the reluctance to treat them differently from financial COIs endangers the validity of science.  Not only are these non-financial threats ignored, but financial interests receive undue attention, resulting in the erosion of public trust in scientific research that is sound.

Professor Saver’s caveats about COI moralism apply beyond biomedical research.  The Exxon Shipping case, the MDL Pocket Guide, and Judge Alsup’s opinion on disclosure of payments to journalists and bloggers signal that courts are well on their way towards selectively and arbitrarily screening out evidence and arguments based upon sponsorship.  What is needed is a whole-hearted commitment to consider and analyze all the available data. Time to shed the blinders.