TORTINI

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

The 4th Reference Manual’s Treatment of Genetic Causes of Disease

January 23rd, 2026

After checking to see whether the new Reference Manual on Scientific Evidence[1] attended to some long overdue corrections, I turned my attention to the substance of the chapter on epidemiology. A cursory comparison between the third[2] and fourth[3] editions of the epidemiology chapter in the Reference Manual a lot of carry over from the third edition, some change in authorship, and at least one interesting change.

The two lawyer authors, Steve Gold and Michael Green, remain, but the authors with reasonable pretense to subject-matter expertise have changed. Gold and Green are both law professors with a long history of commenting on American tort and evidence law. Both are aligned with the lawsuit industry. Previous epidemiology authors, Daryl Michal Freedman and Leon Gordis are now gone from the chapter. Leon Gordis, who had been a chairman of the department of epidemiology, in the Bloomberg School of Public Health, Johns Hopkins University, died in September 2015, after the third edition was published. Daryl Michal Freedman, who been the other subject-matter expert on the third edition’s chapter on epidemiology, has been an epidemiologist with the Biostatistics Branch of the National Cancer Institute, for many years. It is not clear why he left the project.

Replacing Gordis and Freedman are Jonathan Chevrier and Brenda Eskenazi. Chevrier is an associate professor on the faculty of medicine, in the department of epidemiology, in McGill University. The focus of his work is on “common environmental contaminants,” and the role in the development and health of children. Brenda Eskenazi is professor emerita, in the University of California Berkeley School of Public Health, where she is the Director of the Center for Environmental Research and Children’s Health. Eskenazi is a member of a dodgy group known as the Collegium Ramazzini, which was responsible for staging an ex parte presentation of plaintiffs’ expert witnesses to judges presiding in asbestos litigation.[4] Eskenazi was not, however, a member of the Collegium at the time the group conspired with the late Irving Selikoff to pervert the course of justice in American asbestos litigation.

The second significant change is substantive; the fourth edition has added a new subsection to the epidemiology chapter. Comparing the texts of the third and fourth editions of this chapter reveals a new subheading in the new edition:[5]

Genetic and Molecular Epidemiologic Studies

Alas, there is not as much substance to the new subsection, which is less than four pages. Lawyers in the trenches might well have hoped for more substantive treatment of genetic epidemiology, and genetic causation. The chapter’s authors explain their abbreviated treatment with the comment:

“Although commentators have long forecast that the output of genetic and molecular epidemiology would revolutionize causal proof, as of this writing few judicial opinions have addressed these types of studies, and it is far from clear that a revolution is in the offing.”[6] 

The chapter authors are correct that some authors in the past proffered unrealistic predictions of how genetics would supplant correlational studies. Nonetheless, this area has not been as quiescent as the authors’ parsimonious treatment would suggest.

On the question of how prevalent are genetic causation issues, whether raised by plaintiffs or defendants, the chapter might have benefitted from the contributions of a practicing lawyer. Genetic issues come up with some frequency in the litigation of cases involving mesothelioma. The days of plaintiffs who had 30 years of amphibole asbestos exposure in the workplace are largely over. Today’s cases involve little to no exposure, and it stands to reason that the origins of the recently diagnosed cases are different from those diagnosed in the 1970s and 1980s.[7] Genetic cause of mesothelioma is a salient current issue that is passed over in this new Reference Manual.

The authors acknowledge a single birth defects case in which genetic causation was litigated,[8] which was already old news when the last edition of the Manual was published. There are now many more reported cases that cry out for discussion in this under-covered area of the Manual.[9] There are also many cases not reported that have turned on genetic issues. For instance, in some cancer and birth defect cases, the existence of a highly penetrant genetic mutation that could explain the occurrence of a disease completely raises a serious question whether the plaintiff who fails to test for the mutation can possibly have carried his burden of proof.[10] And then there are myriad cases in which the parties have engaged in motion practice, sometimes extended, over access to genetic testing materials.

Genetic issues have arisen in the litigation of high-profile general causation disputes. For instance, the failure to control for genetic effects in epidemiologic studies was a significant issue in the acetaminophen-autism litigation, with both sides presenting geneticists to explain whether the relevant studies were undermined by failure to control for genetic effects.[11]

In the Manual’s epidemiology chapter’s new section on genetics, the authors describe some basic terms and explain that genetic epidemiology may provide evidence for, or against, claims of health effects. The authors’ views come through most clearly in the following short passage:

“Alternatively, genetic epidemiology may reveal associations between genetic variations and a plaintiff’s disease, raising the issue of whether or not a genetic variation may be a competing cause of the disease. This requires assessment of whether the gene–disease association is causal in a general sense, whether it acts independently of the exposure, and whether it is a competing cause in the plaintiff’s specific instance. The extreme, though not typical, example would be a health outcome or disease entirely determined by genetics, 55 as is the case with sickle cell anemia.56[12]

The authors never explain or defend their claim that cases involving diseases caused entirely by genetics are “extreme” and “not typical.” At several points, the authors emphasize that gene-environment interactions are the more prevalent determinants of diseases.[13] If we were to catalog the currently known genetic determinants of diseases, the authors may be correct on a percentage basis, but the issue in any given case is whether the disease or harm claimed by the plaintiff is one of the “extreme” cases of complete genetic causation, or an instance of genetic susceptibility. The authors’ generalization, even if it were correct, would not be very helpful or informative for any specific case.

Perhaps even more important for lawyers, there is a substantive issue on which the new chapter manages to provide confusing guidance. The epidemiology chapter appears to create a false dichotomy between rare, highly penetrant genetic mutations that are uncommon causes of certain diseases, and the more prevalent genetic mutations and polymorphisms that leave persons more susceptible to the deleterious effects of exogenous exposures to toxic chemicals.[14] There is, however, another scenario omitted in the chapter’s discussion of genetic causation. Genetic mutations and polymorphisms may leave persons susceptible to normal, endogenous chemicals, stochastic cellular events, and biological processes that result in diseases such as cancers. In other words, the knee-jerk reflex to invoke exogenous, external toxic chemical exposures promotes a false dichotomy and obscures the obvious implication that susceptibility mutations and polymorphisms may lead to cancer without environmental exposures to harmful chemicals.[15]

The number of endogenous events leading to DNA alterations is enormous, and requires us to rethink the mantra that attributes chronic diseases to gene-environment interaction. At the very least, we need to stop thinking of “environment” as chemical exposures from without ourselves. The epidemiology chapter authors, like many writers, point to external chemical exposures as the culprits in gene-environment reactions, but they ignore the normal, endogenous events that lead to DNA damage, for which genetic susceptibility may be relevant. Mutations that result in increased susceptibility to cancer may affect DNA alterations from both endogenous and metabolic factors as well as from exposures to external chemicals.

Ignorance is never a good thing, and the chapter does the bar and bench a disservice in not adequately exploring genetic susceptibility in view of both exogenous and endogenous exposures that may be responsible for chronic diseases, such as cancers.


[1] National Academies of Sciences, Engineering, and Medicine & Federal Judicial Center, REFERENCE MANUAL ON SCIENTIFIC EVIDENCE (4th ed. 2025) (cited as RMSE 4th ed.)

[2] Michael D. Green, D. Michal Freedman & Leon Gordis, Reference Guide on Epidemiology, 549, in RMSE 3rd ed.

[3] Steve C. Gold, Michael D. Green, Jonathan Chevrier, & Brenda Eskenazi, Reference Guide on Epidemiology, in RMSE 4th ed.

[4] See In re School Asbestos Litigation, 977 F.2d 764 (3d Cir. 1992). See also Cathleen M. Devlin, Disqualification of Federal Judges – Third Circuit Orders District Judge James McGirr Kelly to Disqualify Himself So As To Preserve ‘The Appearance of Justice’ Under 28 U.S.C. § 455 – In re School Asbestos Litigation (1992), 38 VILL. L. REV. 1219 (1993); Bruce A. Green, May Judges Attend Privately Funded Educational Programs? Should Judicial Education Be Privatized?:  Questions of Judicial Ethics and Policy, 29 FORDHAM URB. L. J. 941, 996-98 (2002).

[5] Steve Gold, et al., Reference Guide on Epidemiology, at 914, in RMSE 4th ed.

[6] Id. at 916.

[7] ToxicoGenomica, The Litigator’s Guide to Using Genomics in a Toxic Tort Case (2018).

[8] Id. at 917 & n.55 (citing Bowen v. E.I. Du Pont de Nemours & Co., No. CIV.A. 97C-06-194 CH, 2005 WL 1952859 (Del. Super. Ct. June 23, 2005), aff’d, 906 A.2d 787 (Del. 2006) (discussing the importance of a test for a genetic mutation, which was the defense’s alternative causation theory to plaintiff’s claim that a toxic exposure caused the birth defect at issue). The authors fail to mention that the Bowen case was actually dismissed.

[9] See, e.g., Oliver v. Sec’y Health & Human Servs., 900 F.3d 1357 (Fed. Cir. 2018); Ortega v. United States, 2021 WL 4477896, 2021 U.S. Dist. LEXIS 188969 (N.D.Ill. Sept. 30, 2021); Vanslembrouck ex rel. Braverman v. Halperin, 2014 WL 5462596 (Mich. App. 2014).

[10] See, e.g., Halter v. Boehringer Ingelheim Pharms. Inc., no. 2023-L-001382, Cir. Ct. Cook Cty., Illinois, jury verdict (Aug. 27, 2025) (defense verdict in colorectal cancer case in which plaintiff failed to test for genetic mutation); see also Lauraann Wood, Boehringer Wins Another Zantac Cancer Trial In Illinois, LAW360, Chicago (Aug. 27, 2025).

[11] See, e.g., In re Acetaminophen – ASD-ADHD Prods. Liab. Litig., 707 F.Supp.3d 309, 320  (S.D.N.Y. 2023).

[12] Id. at 916-17 (emphasis added).

[13] Id. at 915.

[14] See, e.g., id. at 967n.190, citing McMillan v. Dep’t of Veterans Affairs, 294 F. Supp. 2d 305, 312 (E.D.N.Y. 2003) (“It is generally accepted that genetic susceptibility plays a key role in determining the adverse effects of environmental chemicals. . . . [I]f polymorphisms of the gene encoding the AhR [protein] exist in humans as they do in laboratory animals, some people would be at greater risk or at lesser risk for the toxic and carcinogenic effects of TCDD [dioxin].”).

[15] See Edward J. Calabrese, Changing the paradigm: The biggest polluter and threat to your health is your body, J. OCCUP. & ENVT’L HYG. (2025), published on-line, ahead of print.

Signature Diseases in the New Reference Manual

January 16th, 2026

The third edition of the Reference Manual on Scientific Evidence[1] had some problems with its discussion of so-called signature diseases.[2] There was a distinct need for the  epidemiology chapter in particular to improve in its fourth edition[3] on the issue of so-called signature diseases, diseases caused by only a single cause. The third edition carved out a limited exception to its questionable generalization that epidemiology had nothing useful to say about specific causation by stating that some diseases do not occur without exposure to a specific chemical or substance.

The new, fourth edition carries forward its assertion that “[t]here are some diseases that do not occur without exposure to an agent; these are known as signature diseases.”[4] And in a footnote, the authors of the epidemiology chapter, fourth edition, attempt to explain:

“There are, however, some diseases that do not occur without exposure to a given toxic agent. This is the same as saying that the toxic agent is a necessary cause for the disease, and the disease is sometimes referred to as a signature disease (also, the agent is pathognomonic) because the existence of the disease necessarily implies the causal role of the agent. Two examples are asbestosis, which is a signature disease for asbestos, and vaginal adenocarcinoma (in young adult women), which is a signature disease for in utero DES exposure. See Kenneth S. Abraham & Richard A. Merrill, Scientific Uncertainty in the Courts, in Issues Sci. & Tech. 93, 101 (1986).”[5]

Much of this language in the footnote is repeated from the third edition, as is the citation to the article by Abraham and Merrill. That article was written by lawyers, not scientists, and is now 40 years old, inaccurate and out of date.

With respect to asbestosis, the epidemiology chapter is correct, at least in part. By definition, only asbestos can cause asbestosis, but asbestosis presents clinically in ways that are indistinguishable in many cases from idiopathic pulmonary fibrosis and other interstitial fibrotic diseases of the lungs. Over the years, the diagnostic criteria for asbestosis have changed, but these criteria have always had a specificity and sensitivity less than 100%. Saying that a case of asbestosis must have been caused by asbestos begs the clinical question whether the case really is asbestosis. The situation might be clearer for a pathology diagnosis of asbestosis, but even then there is often the problem of coincidental findings of asbestos bodies in the presence of interstitial fibrosis from another cause.

On the other hand, the chapter’s characterization of vaginal adenocarcinoma as a signature disease of in utero DES exposure is clearly not correct.  Although this cancer in young women is rather rare, there is a baseline risk that allows the calculation of relative risks for young women exposed in utero.[6] In older women, the relative risks are lower because the baseline risks are higher, and because the effect of DES is diminished for older onset cases.[7] The disease, however, was known before the use of DES in pregnant women, which began after World War II,[8] and thus not an apt or accurate example of signature disease.

The Reference Manual should really not weigh in on controversies that may arise in courtroom litigations, unless it has a very solid basis. Here the chapter on epidemiology cited to a decades old article, by lawyers, on a technical topic. The proposition about DES was readily falsified by a wee bit of research in PubMed.


[1] National Academies of Sciences, Engineering, and Medicine & Federal Judicial Center, REFERENCE MANUAL ON SCIENTIFIC EVIDENCE (3rd ed. 2011) (cited as RMSE 3rd ed.)

[2] See Schachtman, Reference Manual – Desiderata for 4th Edition – Part I – Signature Diseases, TORTINI (Jan. 30, 2023); see also Reference Manual on Scientific Evidence v4.0 (Feb. 28, 2021); Reference Manual on Scientific Evidence – 3rd Edition is Past Its Expiry (Oct. 17, 2021).

[3] National Academies of Sciences, Engineering, and Medicine & Federal Judicial Center, REFERENCE MANUAL ON SCIENTIFIC EVIDENCE (4th ed. 2025) (cited as RMSE 4th ed.).

[4] RMSE 4th ed. at 927-28 n.90.

[5] RMSE 4th at 990 n.274, citing Kenneth S. Abraham & Richard A. Merrill, Scientific Uncertainty in the Courts, 2 ISSUES SCI. & TECH. 93, 101 (Winter 1986). Thankfully, the new epidemiology chapter did not put its finger on the scale about the now discredited view that mesothelioma is a signature disease of asbestos exposure. See Michele Carbone, Harvey Pass, et al., “Medical and Surgical Care of Patients With Mesothelioma and Their Relatives Carrying Germline BAP1 Mutations,” 17 J. THORACIC ONCOL. 873 (2022). See also Mitchell Cheung, et al., Novel LRRK2 mutations and other rare, non-BAP1-related candidate tumor predisposition gene variants in high-risk cancer families with mesothelioma and other tumors, 30 HUMAN MOL. GENETICS 1750 (2021); Thomas Wiesner, et al., “Toward an Improved Definition of the Tumor Spectrum Associated With BAP1 Germline Mutations,” 30 J. CLIN. ONCOL. e337 (2012); Alexandra M. Haugh, et al., Genotypic and Phenotypic Features of BAP1 Cancer Syndrome: A Report of 8 New Families and Review of Cases in the Literature, 153 J.AM. MED. ASS’N DERMATOL. 999 (2017).

[6] See, e.g., Kadir Güzin, et al.,Primary clear cell carcinoma of the vagina that is not related to in utero diethylstilbestrol use,” 3 GYNECOL. SURG. 281 (2006).

[7] Janneke Verloop, et al., Cancer risk in DES daughters, 21 CANCER CAUSES & CONTROL 999 (2010).

[8] See Risk Factors for Vaginal CancerAmerican Cancer Soc’y website (last visited Jan. 16, 2026).

Reference Manual 4th Edition Corrects Some, Not All, Mistakes on Confidence Intervals

January 9th, 2026

So now that the new, fourth, edition of the Reference Manual on Scientific Evidence,[1] has been released, inquiring minds may want to know whether it has corrected errors in the previous, third, edition.[2] The authors of the new edition have had 14 years to ponder and reflect upon errors and to correct them.

Judges and lawyers look to the Manual for guidance and understanding of basic concepts, and the first three editions contained significant errors in addressing statistical concepts. There is probably no better place to jump in to see whether the new edition has corrected the prevalent mistakes in defining the statistical concept of a confidence interval, which was botched in several chapters in the third edition.[3] The concept of a confidence interval is important in many statistical applications, but it is especially important in the interpretation of epidemiologic studies.

Contrition is good for the soul. The new edition, in places, evinces an awareness that earlier editions had misled readers, and that the fourth edition needed to do better.  And in several key places, including in particular the chapter, the fourth edition has improved in its discussion of confidence intervals.

Professor David Kaye has two chapters in the new edition, one on DNA evidence, and another chapter, with Professor Hal Stern, on statistical evidence.[4] Kaye is a careful writer with substantial statistical expertise. His contributions to the third edition were anodyne treatments of statistical concepts, and his chapters in the new edition seem excellent as well upon first reading. In his chapter on DNA evidence, Kaye alludes to the misunderstandings and misrepresentations of the confidence interval,[5] and in his chapter on statistical evidence, Kaye, along with Stern, gives careful definitions and explications of confidence intervals.

Kaye and Stern call out several cases, frequently cited, for having given clearly incorrect definitions of confidence intervals. This sort of candor to the court is necessary if judges, and lawyers, are going to correct bad practices.[6] The statistics chapter in the fourth edition also does not shy away from calling out the authors of another chapter [epidemiology] in the Reference Manual’s third edition for having given erroneous definitions:

“Language from another reference guide in the previous edition of this Reference Manual that is often quoted may inadvertently convey the incorrect impression that a confidence coefficient such as 95% refers to the percentage of results in (hypothetically) repeated studies that would be expected to lie within the interval reported in the study before the court.”[7]

A very gentle criticism indeed; the epidemiology chapter was manifestly incorrect, and we can all agree that its error was negligent, not intentional. The epidemiology chapter from the third edition did not merely convey the incorrect impression; that chapter contained erroneous definitions of confidence intervals.

Kaye and Sterne correctly note that a given confidence interval “does not give the probability that the unknown parameter lies within the confidence interval.”[8] And they helpfully point out that there is no tendency for the point estimate near the center of a confidence interval to be closer to the true value than any other value within the interval.[9]

The authors of the new edition’s chapter on epidemiology obviously got the message from Professors Kaye and Sterne.[10] Fourth time is a charm. The epidemiology chapter in the third edition had been a mess on statistical issues.[11] Without any acknowledgment or confession of error committed in the first three editions, the authors of the epidemiology chapter in the fourth edition now note:

“Just as the p-value does not provide the probability that the risk estimate found in a study is correct, the confidence interval does not provide the range within which the true risk is likely to lie. In other words, it is a misconception to interpret a 95% confidence interval as representing an interval within which the true value has a 95% probability of being found.”[12]

Unfortunately, in the glossary at the end of the new edition’s epidemiology chapter, the erroneous definition of confidence interval was carried forward from the third edition, without change or correction:

confidence interval. A range of values that reflects random error. Thus, if a confidence level of 0.95 is selected for a study, 95% of similar studies would result in the true relative risk falling within the confidence interval.”[13]

What the authors no doubt meant to write was that:

“95% of similar studies would result in the true relative risk falling within the confidence intervals.”

By putting “interval” in the singular, the authors fell into the trap described by Professors Kaye and Hall, and into the error that the previous chapters on epidemiology committed.

The new edition of the Reference Manual appears to suffer, at least on this statistical issue, from the lack of high-level editing across chapters.  The interaction between authors of the statistics and the epidemiology chapters sorted out a serious error, but the error pops up in new chapters. Michael Weisberg and Anastasia Thanukos have an introductory chapter on How Science Works, which crudely and incorrectly describes confidence intervals:

“Uncertainty and error are generally expressed as a range, within which we are confident that, if the study were repeated, the new result would fall. Scientists often use a 95% confidence interval for this purpose.”[14]

Confidence intervals model only random error, and the “range” around one point estimate does not give us “confidence” that the next point estimate would fall into that range.

The chapter on regression analyses in third edition of the Reference Manual incorrectly defined confidence intervals.[15] Alas the fourth edition did not auto-correct:

“Loosely speaking, a confidence interval represents an interval of values in which the true value of a regression coefficient falls within some pre-specified probability (where the true value is the estimate that would be obtained from the same model with a very large sample).”[16]

Why the authors of a highly technical chapter chose to speak loosely, rather than accurately, is a mystery. All the authors of the regression chapter had to do was refer to the accurate, helpful definitions in the statistics chapter.

Why should we care about the Reference Manual’s misleading, incorrect definitions of confidence intervals (or p-values for that matter)? The erroneous definitions and misuses typically place a Bayesian interpretation upon the confidence interval by claiming that the coefficient of confidence (typically 95% when alpha is set at 0.05) states the probability that the parameter, the true population measure, falls within the interval around the point estimate. This misinterpretation might suffice for a Bayesian 95% credible interval, but almost invariably the calculation under discussion is the point estimate ± 1.96 standard errors. Good statistics, like good grammar, costs nothing.

Whether the conflation of confidence intervals with credible intervals results from ignorance or willful efforts to mislead, it is wrong.  And the conflation is part of a long-running rhetorical campaign to mislead about the meaning of the burden of proof and statistical significance in order to abandon statistical tests, and to green-light precautionary principle judgments as “scientific.”[17]

In past posts, I have cited and quoted any number of scientists and lawyers who have engaged in the effort, either intentional or negligent, to mislead readers about the nature of science, by idealizing and falsely elevating the burden of proof in science, and declaring it to be different from the legal and regulatory burden of proof.[18]

To pick one particularly notorious author, consider junk science writer Naomi Oreskes.[19] In her 2010 book, Oreskes declares:

“The 95 percent confidence standard means that there is only 1 chance in 20 that you believe something that isn’t true.

* * * * *

That is a very high bar. It reflects a scientific worldview in which skepticism is a virtue, credulity is not.”[20]

In fact, statistics, science, and law, the confidence interval has nothing to do with the burden of proof; rather it reflects the precision of a single point estimate. Truth is a virtue that may be lost on the likes of Naomi Oreskes, but it is essential to litigating scientific issues. Given that many lawyers in the past had cited the Reference Manual’s chapter on epidemiology for its incorrect definitions of the statistical confidence interval, we should rejoice that this one error has been corrected.


[1] National Academies of Sciences, Engineering, and Medicine & Federal Judicial Center, REFERENCE MANUAL ON SCIENTIFIC EVIDENCE (4th ed. 2025) (cited as RMSE 4th ed.)

[2] National Academies of Sciences, Engineering, and Medicine & Federal Judicial Center, REFERENCE MANUAL ON SCIENTIFIC EVIDENCE (3rd ed. 2011) (cited as RMSE 3rd ed.)

[3] See Nathan Schachtman, Reference Manual – Desiderata for 4th Edition – Part IV – Confidence Intervals, TORTINI (Feb. 10, 2023).

[4] In RMSE 3rd ed., Professor Kaye, along with David Freedman, wrote the chapter on statistical evidence; the two gave careful definitions and explications of confidence intervals.  Professor Freedman sadly died before the third edition was released, and he is replaced by Hal Stern in the chapter on statistics in the fourth edition.

[5] David H. Kaye, Reference Guide on Human DNA Identification Evidence in RMSE 4th ed. at 261, (noting that “the meaning of a confidence interval is subtle, and the estimate commonly is misconstrued”).

[6] See Kaye & Sterne, RMSE 4th ed. at 511 n.125 (citing Turpin v. Merrell Dow Pharm., Inc., 959 F.2d 1349, 1353 (6th Cir. 1992) (“If a confidence interval of ‘95 percent between 0.8 and 3.10 is cited, this means that random repetition of the study should produce, 95 percent of the time, a relative risk somewhere between 0.8 and 3.10.”); Garcia v. Tyson Foods, Inc., 890 F. Supp. 2d 1273, 1285 (D. Kan. 2012) (“Dr. Radwin testified that his study was conducted within a confidence interval of 95 — that is ‘if I did this study over and over again, 95 out of a hundred times I would  expect to get an average between that interval.’”); In re Silicone Gel Breast Implants Prods. Liab. Litig., 318 F. Supp. 2d 879, 897 (C.D. Cal. 2004) (“a margin of error between 0.5 and 8.0 at the 95% confidence level . . . means that 95 times out of 100 a study of that type would yield a relative risk value somewhere between 0.5 and 8.0”)).

[7] See Kaye & Sterne, RMSE 4th ed. at 511 n.125 (citing Rhyne v. U.S. Steel  Corp., 474 F. Supp. 3d 733, 744 (W.D.N.C. 2020) (“‘If a 95% confidence interval is specified, the range encompasses the results we would expect 95% of the time if samples for new studies were repeatedly drawn from the population.’ Reference Guide on Epidemiology, at 580.”).

[8] Kaye & Sterne, RMSE 4th ed. at 512 & n. 126 (citing additional errant judicial decisions, and Geoff Cumming & Robert Maillardet, Confidence Intervals and Replication: Where Will the Next Mean Fall?, 11 PSYCH. METHODS 217 (2006).)

[9] Id. at 512.

[10] Steve C. Gold, Michael D. Green, Jonathan Chevrier, & Brenda Eskenazi, Reference Guide on Epidemiology, in RMSE 4th ed. at 897

[11] Michael D. Green, D. Michal Freedman & Leon Gordis, Reference Guide on Epidemiology, 549, 573, 580, in RMSE 3rd ed.

[12] Steve C. Gold, Michael D. Green, Jonathan Chevrier, & Brenda Eskenazi, Reference Guide on Epidemiology, RMSE 4th ed. at 897, 939.

[13] Id. at 1011.

[14] Michael Weisberg & Anastasia Thanukos, How Science Works , in RMSE 4th ed. at 47, 90.

[15] Daniel Rubinfeld, Reference Guide on Multiple Regression, RMSE 3rd ed. at 303, 342, 352.

[16] Daniel Rubinfeld & David Card, Reference Guide on Multiple Regression and Advanced Statistical Models, in RMSE 4th ed. at 577, 613.

[17] Schachtman, Rhetorical Strategy in Characterizing Scientific Burdens of Proof, TORTINI (Nov. 11, 2014);

[18] See, e.g., Kevin C. Elliott & David B. Resnik, Science, Policy, and the Transparency of Values, 122 ENVT’L HEALTH PERSP. 647 (2014) (exemplifying the rhetorical strategy that idealizes and elevates a burden of proof in science, and then declaring it to be different from legal and regulatory burdens of proof).

[19] Schachtman, Playing Dumb on Statistical Significance, TORTINI (Jan. 4, 2015); The Rhetoric of Playing Dumb on Statistical Significance – Further Comments on Oreskes, TORTINI (Jan. 17, 2015).

[20] Naomi Oreskes & Erik M. Conway, MERCHANTS OF DOUBT: HOW A HANDFUL OF SCIENTISTS OBSCURED THE TRUTH ON ISSUES FROM TOBACCO SMOKE TO GLOBAL WARMING at 156-57 (2010).

A New Year, A New Reference Manual

January 5th, 2026

The fourth edition of the Reference Manual on Scientific Evidence was quietly released in the waning hours of 2025, in the twilight of American democracy.[1] The Manual had been slated to be published in 2023, but that date slid to 2024, and then to 2025.  Perhaps the change in directorship of the Federal Judicial Center slowed things up. (Judge Robin Rosenberg of Zantac fame is now the Director)

The new volume is available for download at:

https://www.nationalacademies.org/publications/26919

Although I was a reviewer of one chapter of the Manual, I am just seeing this new edition for the first time today. The basic structure of the volume has not changed, although it has now grown to over 1,600 pages. Many of the key chapters on statistics, epidemiology, toxicology, and medical testimony are carried over from previous editions, with some new authors added and some previous authors no longer participating. In addition, there are some new chapters on exposure science, artificial intelligence, climate science, mental health, neuroscience, and eyewitness identification.

The individual chapters and authors in the new edition of the Manual are:

Liesa L. Richter & Daniel J. Capra, The Admissibility of Expert Testimony, at 1.

Michael Weisberg & Anastasia Thanukos, How Science Works, at 47

Valena E. Beety, Jane Campbell Moriarty, & Andrea L. Roth, Reference Guide on Forensic Feature Comparison Evidence, at 113

David H. Kaye, Reference Guide on Human DNA Identification Evidence, at 207

Thomas D. Albright & Brandon L. Garrett, Reference Guide on Eyewitness Identification, at 361

David H. Kaye & Hal S. Stern, Reference Guide on Statistics and Research Methods, at 463

Daniel L. Rubinfeld & David Card, Reference Guide on Multiple Regression and Advanced Statistical Models, at 577

Shari Seidman Diamond, Matthew Kugler, & James N. Druckman, Reference Guide on Survey Research, at 681

Mark A. Allen, Carlos Brain, & Filipe Lacerda, Reference Guide on Estimation of Economic Damages, at 749

Prologue to the Reference Guide on Exposure Science and Exposure Assessment, the Reference Guide on Epidemiology, and the Reference Guide on Toxicology, at 829i

Elizabeth Marder & Joseph V. Rodricks, Reference Guide on Exposure Science and Exposure Assessment, at 831

Steve C. Gold, Michael D. Green, Jonathan Chevrier, & Brenda Eskenazi, Reference Guide on Epidemiology, at 897

David L. Eaton, Bernard D. Goldstein, & Mary Sue Henifin, Reference Guide on Toxicology, at 1027

John B. Wong, Lawrence O. Gostin, & Oscar A. Cabrera, Reference Guide on Medical Testimony, at 1105

Henry T. Greely & Nita A. Farahany, Reference Guide on Neuroscience, at 1185

Kirk Heilbrun, David DeMatteo, & Paul S. Appelbaum, Reference Guide on Mental Health Evidence, at 1269

Chaouki T. Abdallah, Bert Black, & Edl Schamiloglu, Reference Guide on Engineering, at 1353

Brian N. Levine, Joanne Pasquarelli, & Clay Shields, Reference Guide on Computer Science, at 1409

James E. Baker & Laurie N. Hobart, Reference Guide on Artificial Intelligence, at 1481

Jessica Wentz & Radley Horton, Reference Guide on Climate Science, at 1561

Some quick comments on changes in authorship in some of the chapters. Bernard Goldstein, a member of the dodgy Collegium Ramazzini, remains an author of the toxicology chapter in the new edition. David Eaton, however, has been added. Professor Eaton was the president of the Society of Toxicology for many years, and perhaps he has brought some balance to the new edition’s work on toxicology.

An author of the statistics chapter, David Kaye, is also the sole author of the chapter on DNA evidence. Professor Kaye is a distinguished scholar of DNA evidence with serious statistical expertise. David Freedman had been a co-author of the statistics chapter in the third edition, but sadly Professor Freedman died before the third edition was published. Freedman is replaced by Hal Stern, an accomplished statistician from the University of California.

The chapter on epidemiology lost Leon Gordis, who died in 2015. The chapter in the fourth edition has the return of law professors Steve C. Gold and Michael D. Green, whose pro-plaintiff biases are well known, along with two new authors, epidemiology professors Jonathan Chevrier, & Brenda Eskenazi. Like Goldstein, Eskenazi is a fellow of the Collegium Ramazzini.

The Reference Manual, for better or worse, has had substantial influence on the litigation of scientific and technical issues in federal court, and in some state courts as well. I hope to write more substantively about the new edition in 2026.


[1] National Academies of Sciences, Engineering, and Medicine & Federal Judicial Center, Reference Manual on Scientific Evidence (4th ed. 2025).