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Sampling

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Overview

Developing appropriate methodologies to draw reliable conclusions

An alternative to big data analytics, statistical sampling may be preferred when it is not feasible to assess all elements of a population, such as when key information is only available in hard copy records that are expensive and take time to obtain. Statistical sampling offers a scientifically reliable and cost-effective approach to learning about entire populations from a more manageable subset or from samples. Our team has significant experience and expertise designing samples and developing data collection protocols to draw statistically valid conclusions, whether it is in consulting, investigation, arbitration, or litigation settings. 

Case highlights 

  • In New Jersey Primary Care Association, Inc. v. State of New Jersey Department of Human Services, et al., Amanda Kurzendoerfer advised the plaintiff regarding the allocation of settlement proceeds to cover previously unpaid Medicaid claims among Federally Qualified Health Centers (FQHC). The work involved developing a statistical sampling strategy to review claims and determine a settlement allocation based on the total amount of unpaid claims for each FQHC.
  • Angela Rockwell submitted an expert affidavit rebutting a proposed statistical sampling plan in a matter involving usual, customary, and reasonable rates for out-of-network emergency services on behalf of a national health insurer. Dr. Rockwell also submitted expert declarations assessing extrapolated damages and interest calculations based on a sample of claims in a reinsurance arbitration on behalf of a large international insurance company.
  • On behalf of a leading healthcare provider in an arbitration focused on a chronic healthcare condition, submitted an expert affidavit on a statistical sampling protocol related to patient records that was selected by the arbitration panel.
  • In United States of America ex rel. Gwen Thrower, Plaintiff, v. Academy Mortgage Corp., developed a framework for calculating damages that relied on our expertise in statistical sampling. After Christopher Bennett submitted his report and provided deposition testimony, the Department of Justice announced that Academy will pay $38.5 million to resolve the claims.
  • Provided expert testimony on sampling issues in several asbestos-related bankruptcy proceedings in the Western District of North Carolina. In In re Aldrich Pump LLC, et al., provided testimony on behalf of Debtors, comparing the benefits of statistical sampling versus reliance on an entire population of data. In particular, Charles Mullin argued that the primary benefit of sampling is to reduce the costs of data production—such as when documents are only available in hard-copy form—which may be unnecessary when population-level data are available electronically. In In re Bestwall, LLC, Jorge Gallardo-García outlined a sampling methodology for drawing a representative and efficient sample of mesothelioma claimants from the Debtor’s claimant population in response to a court-ordered request for such a sample.
  • ResCap Liquidating Trust actions. On behalf of ResCap Liquidating Trust, extrapolated defect rates and assessed damages arising from various originators’ sale of defective mortgage loans to ResCap. To quantify and allocate damages among the various originators, developed a statistical sampling protocol that could be used to reliably estimate defect rates and a large-scale loan-performance database of approximately 2 million loans that could be used to reliably assess the relative performance of originators’ loans.
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