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Two Faces of Causality: A Small
Case Study of the Admission of
Scientific Evidence to Show
Causality in a Bias and a Toxic
Tort Case in the 4th Circuit
Christina Kirk Pikas
LBSC 735: Legal Issues in Information
Management
December 11, 2002
Overview
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Review of the efforts made to form the
admissibility of scientific evidence
Discussion of causality and the scientific
and the statistical methods used to prove
Case studies of two cases:
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Product liability
Pay discrimination
Admission of Expert Evidence
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19th century
Frye (1923)
Federal Rules of Evidence (1975)
Daubert Trilogy
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Daubert (1993)
Joiner (1997)
Kumho (1999)
Causality
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Definition: “The principle of causal relationship;
the relation between cause and effect” (Black’s
Law Dictionary)
Cause: “To bring about or effect” (Black’s Law
Dictionary)
Correlation, association, or statistically
significant relationship is not enough
Primary issue in
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Toxic torts
Product liability
Discrimination
General vs. Specific Causality
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General (examples: toxicology, epidemiology)
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anecdotal evidence
observational studies
controlled experiments
Specific
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Treating Doctor
Series of specific details such as
•Temporal relationship
•Strength and specificity of
association
•Dose-response relationship
•Consistent with other knowledge
•Biological plausibility
•Consideration of alternate
hypotheses
•Cessation of exposure
Case 1: Nettles v. Proctor &
Gamble
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Ms. Nettles used Vicks Sinex Nasal Spray
and later became blind
A neuro-opthalmologist was produced to
give evidence on her case
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No studies existed linking the main ingredient
to her condition
Only temporal connection was found
As per Joiner – court did was neither
arbitrary or capricious, decision was
affirmed
Case 2: Smith, et al v. Virginia
Commonwealth University
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VCU employed a committee to determine
if there was a discrepancy in pay between
male and female tenure and tenure-track
professors
The committee used a multiple regression
analysis and determined that there was a
$1,300 difference. Another committee
was started to review CVs and give
deserving female employees appropriate
raises.
Case 2: continued
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Plaintiffs Allege
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Not fair because raises based only on gender
Inflated pool – more males had been
administrators and therefore had higher pay
Analysis not valid because did not take into
account major factors relating to pay, namely
performance
Trial Court
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Proxies were sufficient, regression study valid,
pay handed out fairly, to correct inequity
Summary Judgment awarded to VCU
Case 2: Continued
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Appeals Court
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Regression did not take into account
performance factors, not invalid, but probative
value in question
If material issues exist, should not have been
a Summary Judgment, reversed.
Analysis
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If the lower court had employed Daubert
factors, the summary judgment was correct
The initial study was invalid – it poorly fit the
real situation under study
Conclusion
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Complexity of new cases, commingling of
evidence, junk science make the
gatekeeper role very important
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Judges see expert evidence 90 days before
trial
Many courses, books, and studies exists to
help train judges
Judges can appoint neutral experts to help
interpret the evidence
More Conclusions
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Scientific methods and statistics are being
used for purposes for which they were not
designed
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Statistics don’t prove anything – give relative
probability
Toxicology and epidemiology – give relative
risk
Statistical significance and practical
significance are not the same
Finally
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Daubert provides a useful framework if
flexibly employed
Resulting summary judgments save time
and money
It’s still easy to lie with statistics