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Posts Tagged ‘statistics’

I’m very excited to be speaking at a Strafford Publications CLE webinar tomorrow entitled: Statistics in Class Action Litigation: Admissibility, Expert Witnesses and Impact of Comcast v. Behrend.   The program is scheduled for June 18, 2013 at  1:00pm-2:30pm EDT.  This is the third iteration of this presentation, which has been updated to offer insights in light of the Supreme Court’s Comcast decision earlier this term.  Brian Troyer of Thompson Hine in Cleveland and Justin Hopson and Rick Preston from Hitachi Consulting in Denver will be co-presenting.  Below is a synopsis of the program.  Click here for more information and to register:

Class certification standards have become more rigorous, and the skillful use of statistical evidence is an important part of class actions. Effectively employing or challenging statistics can make a difference in winning or losing a class certification motion.

Statistical evidence is introduced through expert witness testimony, and Daubert challenges may be an effective strategy. This raises the issue of the scope of the court’s inquiry into the merits at the class certification stage.

The 2011 Wal-Mart v. Dukes Supreme Court ruling underscored the prominent role of statistical evidence in assessing the merits at the certification stage. The Court’s recent Comcast v. Behrend ruling reinforces Dukes regarding merits assessments at class certification, thus impacting the continued role of statistical evidence.

Listen as our experienced panel examines statistical evidence in certification proceedings, the impact of Comcast v. Behrend and related case law, and best practices for using statistics and cross-examining witnesses.

Outline

  1. Role of statistical evidence in support of class certification
  2. Expert testimony and Daubert analysis at class certification stage
  3. Impact of Comcast v. Berhrend and Wal-Mart v. Dukes
  4. Science of statistics and cross-examining the statistics witness

Benefits

The panel will review these and other key questions:

  • What is the impact of Comcast and Dukes upon the use of statistical analysis at class certification?
  • What strategies can counsel use to effectively cross-examine statistics witnesses?
  • What types of statistics can be introduced and what are the proper ways to utilize statistics?

Following the speaker presentations, you’ll have an opportunity to get answers to your specific questions during the interactive Q&A.

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This is the last of six posts summarizing my notes of the six presentations at the ABA’s 16th Annual Class Actions Institute held in October in Chicago.  For more on this excellent conference, see my October 31, November 5, November 6November 18, and December 3 CAB posts.

This year’s Institute was capped off by a presentation and demonstration entitled: “Preparing Early and Often,” State-of-the-Art Strategies for Managing Class Action Experts.  Andrew J. McGuiness moderated the panel, which consisted of expert economists Dr. Janet S. Netz and Dr. James Langenfeld, attorneys Mary Jane Fait and Laurie A. Novion, and U.S. District Court Judge Gerald E. Rosen.  The panel’s insightful tips were highlighted by vignettes in the form of mock examinations of the two experts. 

Daubert analysis of proposed expert testimony is required at the class certification, a question on which the Supreme Court may shed some light when it rules on Comcast v. Behrend later this term.  At the moment, circuits that require a Daubert analysis include the Fourth, Seventh, Ninth, and Eleventh Circuits.  The Sixth and Eighth Circuits have both adopted a Daubert-lite standard, while the Fifth Circuit has taken a “Daubert Maybe ” or “Daubert I don’t know” approach to the question.

The vignettes illustrated some of the key potential lines of attack on a plaintiff’s or a defendant’s expert’s opinions presented in support of or in opposition to class certification.  They include (but are not limited to): 1) whether the expert relied on a reliable dataset; 2) whether there is a formulaic basis for calculating damages; 3) whether there are any inconsistencies between the defendant’s own transactional data and outside data, such as market research data; 4) whether any individual variation in the data can be explained in a systemic way; and 5) whether a regression analysis or other analytical model is a valid way of evaluating the data or its causal connection to the defendant’s alleged misconduct.

Both the vignettes and the panelists’ observations served to reinforce how important it is for the lawyer to present an expert’s testimony in a way so that the judge understands the evidence.

One key practice tip offered by the panel was to consider using a consulting expert before turning to a testifying expert.  This way, different models or modes of analysis can be tested without fear of tainting the conclusions of the testifying expert or unnecessarily exposing the testifying expert to impeachment or cross-examination. 

However, that does not mean that it is not necessary to make full disclosure to the testifying expert about the material facts and legal issues in the case.  A common frustration that experts have with lawyers is they oftentimes fail to provide a fair and clear picture of the facts or applicable law, leading the expert to an opinion that is at odds with the facts or irrelevant to the issues in the case.  At minimum, this can put the expert in an awkward position and undermine the attorney’s client’s chances for success.  At worst, it can both lead to an adverse decision and cause undeserved and lasting damage to the expert’s professional reputation.

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In preparing for our webinar on the use of statistics in class actions tomorrow, I discovered that the California Supreme Court has granted review in Duran v. U.S. Bank, a case that could have major implications for the future of statistical sampling as common proof in class actions.  See my April 6, 2012 post titled Trial by Formula, Statistical Sampling, and the Right to Due Process for a summary of the Court of Appeal’s decision, which has lost its precedential effect by virtue of the decision to grant review.  The supreme court’s docket for the case  is available here.   Kimberly Kralowec has posted many of the court documents on her blog, The UCL Practitioner.

The folks at the Litigation Impact Journal have noted that the decision to grant review in Duran was foreshadowed by Justice Werdegar’s concurrence in his own majority opinion in the California Supreme Court’s highly publicized decision last month in Brinker Restaurant Corp. v. Superior Court.  In that concurrence, Justice Werdeger argued that “[r]epresentative testimony, surveys, and statistical analysis all are available as tools to render manageable determinations of the extent of liability [in wage and hour cases].”  In Duran, the court will have an opportunity to explore that issue in more detail.

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It’s not too late to sign up for next Wednesday’s Strafford Publications Webinar, Statistics in Class Action Litigation: Admissibility, Expert Witnesses and Impact of Wal-Mart v. Dukes.  Click the link on the title of the program for more information and to sign up.

For anyone looking for sneak preview, here are the program slides, which were are the result of the joint efforts of my co-presenters, Brian Troyer of Thompson Hine and Rick Preston of Hitachi Consulting, and me.  We hope you can make it!

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I’m not sure that WordPress site statististics would be admissible in a class action as proof of readers’ interest, but the recent CAB site stats do appear to show some level of interest in the topic of statistics in class actions. 

So, readers may be interested in an upcoming Strafford Publications webinar in which I will be participating on May 23, 2012, entitled Statistics in Class Action Litigation: Admissibility, Expert Witnesses and Impact of Wal-Mart v. Dukes.  For those of you who think that title sounds familiar, this is an update of a Strafford webinar held last year shortly after the Dukes decision was announced.  Find out if our predictions then were at all close to the mark. 

Here’s a link to the Strafford page for the webinar, where you can get more information and register:

http://www.straffordpub.com/products/statistics-in-class-action-litigation-admissibility-expert-witnesses-and-impact-of-wal-mart-v-dukes-2012-05-23

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For those of you interested in the topic of statistics in mass and class actions, U. Conn. Law Professor and Mass Tort Litigation Blog contributor Alexandra D. Lahav has written an academic paper on the subject in the Texas Law Review, aptly entitled The Case for “Trial by Formula.”  For Professor Lahav’s synopsis of the paper, a link to the paper, and a brief response to last week’s CAB post on the subject, see this Mass Tort Litigation Blog post.

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Editor’s Note: This is a joint post for ClassActionBlawg and the newly-launched Baker Hostetler Class Action Lawsuit Defense Blog.  Be sure to bookmark the Baker Hostetler blog at www.classactionlawsuitdefense.com for the latest in class action trends and decisions.

A common temptation in class action litigation is to fashion procedures based on “rough justice” to avoid overburdening the courts or attempting to redress alleged mass harm.  Over the past decade, as storage and computing power have increased exponentially, it has become increasingly tempting to use statistical sampling as a proxy for the actual adjudication of facts in class or mass actions.  The idea is that if the facts regarding a statistically significant subset of a class can be evaluated for a particular issue or set of issues, then the results of the evaluation of the sample can be extrapolated across the rest of the class.

One jurisdiction in particular where this approach has gained traction has been California.  There, the use of statistical sampling has been recognized for several years as a means of apportioning damages in some cases.   See Bell v. Farmers Ins. Exchange (2004) 115 Cal.App.4th 715 [9 Cal.Rptr.3d 544] (Bell III).   However, in recent years, plaintiffs have attempted to use statistical sampling as proof of liability, not simply as a means of apportioning damages when liability has been established or (as in Bell III) it is not contested.  This approach was harshly criticized in Part III of Justice Scalia’s majority opinion in Wal-Mart v. Dukes, (notably, this was the portion of the Dukes opinion with which all nine justices concurred):

The Court of Appeals believed that it was possible to replace such proceedings with Trial by Formula. A sample set of the class members would be selected, as to whom liability for sex discrimination and the backpay owing as a result would be determined in depositions supervised by a master. The percentage of claims determined to be valid would then be applied to the entire remaining class, and the number of (presumptively) valid claims thus derived would be multiplied by the average backpay award in the sample set to arrive at the entire class recovery— without further individualized proceedings. [internal citation omitted].  We disapprove that novel project.

Earlier this year, in Duran v. U.S. Bank National Association, No. A125557 & A126827 (Cal. App., Feb.  6, 2012), a division of the California Court of Appeal agreed with the above-quoted dicta in Dukes and rejected an attempt to use statistical sampling to prove liability an a wage and hour class action.  The plaintiff had presented testimony from statistician Richard Drogin, who had also served as an expert for the plaintiffs in Dukes.  Drogin presented a random sampling analysis that purported to estimate the percentage of the defendant’s employees that had been misclassified for purposes of entitlement to overtime pay.  The trial court adopted a sampling approach that was modeled on (but not exactly the same as) Drogin’s proposal.  

The Court of Appeal held that the trial court’s approach was improper and that it violated defendant’s due process rights for a variety of reasons, including that 1) the use of statistics to estimate the total number of employees who had been misclassified deprived the defendant an opportunity to present relevant evidence and individualized defenses as to individual plaintiffs’ alleged misclassification; 2) the court’s statistical methodology was flawed because it arbitrarily used a sample of 20 employees without any basis for concluding that the sample was statistically significant; 3) even the use of sampling as to damages was improper because the methodology used had an unacceptably high margin of error.

The Duran opinion is worthy of careful study for anyone considering the use of statistics in class certification proceedings, both in the employment context and in other types of class actions.  The opinion examines many of the due process problems with allowing proof of liability through statistical sampling, the most significant of which is that it tends to deprive a defendant of presenting evidence in its defense that it would be able to present in an individual case.  It also provides an additional illustration of what the Supreme Court considered an improper “trial by formula” in Dukes.

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