The Witness Box

Commenting on expert evidence, economic damages, and interesting developments in injury, wrongful death, business torts, discrimination, and wage and hour lawsuits

Saturday, November 22, 2008

If you drink you die...

a little earlier that is...

According to life expectancy 1.0 calculators, a person who never drinks (that is never, ever), will life about 5 years longer than a person who drinks 3 or so drinks a day.

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Monday, November 17, 2008

Convenience v. Random Sampling in Wage and Hour

Convience sampling v. Random sampling:

A convenience sample is a sample where individuals are selected, in part or in whole, at the convenience of the researcher. The researcher makes no attempt, or only a limited attempt, to insure that this sample is an accurate representation of some larger group or population.

The classic example of a convenience sample is standing at a shopping mall and selecting shoppers as they walk by to fill out a survey.

In contrast, a random sample is one where the researcher insures (usually through the use of random numbers applied to a list of the entire population) that each member of that population has an equal probability of being selected.

See how convenience samples can potentiallly help improve a random sample 10498-en.pdf

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Monday, November 10, 2008

Race is off-limits factor in wrongful death case

From: Federal Judge Blasts Use of Statistics on Race to Set Damages in Ferry Crash, Anthony Lin, New York Law Journal, October 15, 2008


A Brooklyn federal judge has slammed the use of statistics showing racial differences in life expectancy to determine damages for a catastrophically injured black man.James McMillan was rendered a quadriplegic in the 2003 crash of the New York City-operated Staten Island Ferry. Last month, Eastern District of New York Judge Jack B. Weinstein awarded McMillan damages of $18.3 million.

The city had sought to limit McMillan's damages on a number of grounds, arguing that his past criminal records as much as his race indicated a shorter life expectancy. But Weinstein indicated during trial he would issue a written decision further explaining his reasoning on the race issue.

Issuing that decision Tuesday, Weinstein said the consideration of statistical differences in life expectancy among races in determining damages would be discriminatory and unconstitutional. He noted that a wrongheaded insistence on immutable racial differences had been behind the U.S. Supreme Court's infamous decision in Plessy v. Ferguson, 163 U.S. 537 (1896), which upheld racial segregation under the doctrine of "separate but equal.""Statistical reliance on 'race' leads to such questions as whether Plessy would have been today categorized as 'African American' for life expectancy purposes,"

Weinstein wrote. "In a more recent example, 'racially' characterizing for statistical purposes in a negligence lawsuit the current Democrat Party presidential candidate, born of a 'White' American mother and an 'African' citizen of Kenya, would be considered absurd by most Americans."

The judge also said racial statistics should be rejected on scientific grounds, and he approvingly cited a number of well-known anthropologists who regard race as a social construct rather than a biological fact."Reliance on 'race'-based statistics in estimating life expectancy of individuals for purposes of calculating damages is not scientifically acceptable in our current heterogeneous population,"

Weinstein wrote in McMillan v. City of New York, 03 civ. 6049.Though the judge acknowledged a documented mortality gap between blacks and whites, he said the gap likely owed much to socioeconomic factors masked as "race."

He noted some studies indicating that blacks and whites of equivalent socioeconomic status enjoyed similar longevity.Weinstein said that courts had increasingly moved toward race- and gender-neutral calculations of damages, and observed that racial differences were ignored by Special Master Kenneth R. Feinberg in his administration of the federal September 11th Victim Compensation Fund.The Corporation Counsel's Office declined to comment on Weinstein's decision.

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Sunday, October 26, 2008

The last word on survey evidence in wage and hour cases

What do the courts say about survey evidence?

Take a look at:

sciman00.pdf

Reference Manual on Scientific Evidence, Second Edition 2000, 638 pages

The second edition of Reference Manual on Scientific Evidence has been published and distributed to federal judges.

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Saturday, October 18, 2008

Attack I: Inadmissible Hearsay - a detailed look

Is the bar for wage and hour survey evidence too high?

As mentioned in the last posted the defendant's in Marlo v. UPS attacked the plaintiff's wage and hour survey on several levels. The following discusses the details of the attack.

1. A representative sample was not selected.

First, no precautions were
taken to ensure that only qualified respondents were included in the Telephone
Survey....the Telephone Survey did not ask any questions to ensure that
respondents were qualified to participate in the survey, such as whether they were
currently employed at UPS in one ofthe FTS job positions, or if they ever held one
of the relevant FTS job positions at UPS.


Second, there is no evidence that the respondents who participated in
the Telephone Survey are representative of all class members. Of the 614
"qualified respondents" provided by Plaintiffs counsel, only 160 interviews were
completed. The plaintiff's expert does not provide information about relevant characteristics of the 160 respondents, such as the region or district where they worked, whether they worked as a full-time on-road, hub, or preload supervisor, or the length oftheir employment. fd. Nor does it compare the characteristics of the respondents to the population the Telephone Survey was
intended to represent.

The plaintiff's expert confirmed at deposition that she did not know whether
the sampling frame was representative of the universe, whether the sample was
random from any other larger universe of people who were being surveyed, or
whether the sample was stratified as to any larger list, and that she did nothing at all
to evaluate the representative nature of the sample.

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Friday, October 17, 2008

Attack I: The survey is inadmissible hearsay

Is the bar too high for survey evidence in wage and hour cases?

The defendant's first attack was the survey was inadmissible hearsay of the type not reasonalbly relied on by experts in the field.
According to the defendants:

The results of the Telephone Survey are out-of-court statements by
respondents purportedly discussing their knowledge and application of UPS's
methods and procedures. Plaintiff seeks to use the results ofthe Telephone Survey
to prove the truth of those statements, i.e., that the respondents know and apply
UPS' methods and procedures. This is classic hearsay. FED. R. EVID. 801(c)

Some courts have allowed the admission of survey evidence under the
residual or "catch all" exception to the hearsay rule upon a finding that the survey is
"material; . .. more probative on the issue than any other evidence; and ... has
'circumstantial guarantees of trustworthiness. "

A survey is trustworthy if it "is conducted in accordance with
generally accepted survey principles, and if the results are used in a statistically
correct way, since proper survey and statistical methods are intended to assure a
poll's reliability."

The defendant's attacked the plaintiff's wage and hour survey on several levels. Using the defendant's definition of 'trustworthy' means that a trustworthy survey is one where:

(1) the "universe" was properly defined;
(2) a representative sample of that universe was selected;
(3) the questions to be asked of interviewees were framed in a clear, precise, and nonleading
manner;
(4) sound interview procedures were followed by competent
interviewers who had no knowledge ofthe litigation or the purpose for which the
survey was conducted;
(5) the data gathered was accurately reported;
(6) the data was analyzed in accordance with accepted statistical principles; and
(7) the objectivity of the entire process was ensured.

According to the defendant's motion, the plaintiff's expert's survey did not meet any of these requirements for a sound study.

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Thursday, October 16, 2008

Is the bar too high for survey evidence in wage and hour cases?

So, now that the backdrop for the survey in the Marlo v. UPS case has been laid, what then is the problem? The company that performed the survey had performed numerous surveys...that was their job. In addition, the witness, at least one of them, was the president of the survey company. The other witness was a Ph.D. Industrial Organization professor.

Here is a summary of the defense's motion to exclude the survey. (More discussion in follow-up posts)


However, any opinion or testimony about the Telephone
Survey must be excluded for two separate and independent reasons. First, any such
opinion or testimony is inadmissible because the results of the Telephone Survey
constitute hearsay of a type that is not reasonably relied upon by experts in her
particular field. Second, any such opinion or testimony is inadmissible under
Federal Rule of Evidence 702 and Daubert v. Merrell Dow Pharmaceuticals, Inc.,
509 U.S. 579 (1993), because

(I) the expert does not qualify as an "expert";
(2) the expert's opinion will not assist the trier offact;
and (3) the expert's opinion is not (a) "the
product of reliable principles and methods"; (b) based upon sufficient facts or data;
and (c) based upon a reliable application of principles and methods to the facts of
this case. Thus, any opinion or testimony by the expert about the fact, contents, results,
or purported scientific validity ofthe Telephone Survey must be excluded at trial.

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Wednesday, October 15, 2008

Survey adminstration

Is the bar too high for survey evidence in wage and hour cases?

Here are the details of how the survey was conducted:

SAMPLE

A list of 614 cases was provided. This list was checked for duplicate phone numbers and valid area codes and 64 cases were thrown out. Of the 550 remaining numbers, 166 were unusable, leaving 384 viable phone numbers. The remaining 384 cases we dialed up to 5 attempts in an effort to complete the questionnaire with as many as possible.

INTERVIEWING·
Interviewing took place between the dates of November 18th and November 24",2004. Calling times were scheduled from 6:00-9:00 PST weekdays, 9:00 am-4:00 pm PST on Saturday and 2:00-8:00 PST Sunday.

Interviewing took place at various times during these calling windows. Daytime dialing also occurred on the 220d and 23'd of November.

Interviewing was completed following sound, standard marketing research call center practices Including reading verbatim and administering the interview in a non-biased fashion. 20% of completed interviewers were silently monitored (10% is industry standard). 13% of respondents were called back to confirm qualification and study participation (10% is industry standard).

Supervision ratio was 1 hour for every 3.5 interviewing hours. Industry average is approximately 1:8.
A total of 7 Intervij1wers were briefed and dialed on this study at some time during its 7days in field ranging from 1to 5 during any given shift.

QUESTIONAIRE·

Aquestionnaire wjth 42 yes/no/na questions was provided to ORI, atrue and correct copy of which Is attached hereto ap Exhibit 1. This questionnaire was programmed Into CATI (computer assisted telephone interviewing) software commonly used within the industry to administer telephone interviews. In addition to providing the script and capturing data the software also regulates the phone numbers to be called in reference to callbacks times, resolved vs. non resolved numbers, etc.

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Tuesday, October 14, 2008

Part I : Background on survey in wage and hour case

Is the bar too high for survey evidence in wage and hour cases? Part I


In November 2004, Plaintiff Michael Marlo's counsel of record, John
Furutani, retained a "data collection execution and management" to conduct a telephone survey ("Telephone Survey") of current and former UPS employees.

The survey asked questions related to procedures that the UPS employees followed. The survey also asked about the authority that the UPS employees had to fire, change schedules, etc. of other UPS employees.

Plaintiff intends to offer the expert testimony of the president of the survey firm regarding the fact, content, results, or purported scientific validity of the Telephone Survey.


The survey:

Application of knowledge and training!manager's desires
1) Do you apply your knowledge ofUPS' prescribed procedures when
determining which procedure to follow in a given situation?
2) Are the decisions you make on a daily basis as a UPS full-time supervisor
based on UPS' rules, procedures or methods that you have been trained on?
3) Are the decisions which you routinely make as a UPS full-time supervisor
based on the experience you have gained working for UPS?
4) Have you been traioed in UPS' methods and procedures?
5) Are the decisions which you routinely make as a UPS full-time supervisor
based on the training you have received while working for UPS?
6) Are the decisions of consequence you make in the operation dictated by the
training you have received on the proper procedures and methods?
Training on the methods
7) Do you have the authority to modify training methods if you feel you have a
better way of doing something?
8) Do you train employees on UPS' methods?
9) Do you ever disregard the methods while training?
10) Do you train outside of the prescribed methods?
11) Do you train outside of the prescribed procedures?

12) Do you have the authority to train an employee in your own methods if you
feel they are better than UPS'?
Changing and adherence to goals set by UPS
13) Do you have the authority to unilaterally change the goals set by UPS?
14) Do you have the authority to unilaterally change the goals given to you by
Industrial Engineering (IE)?
15) As a full-time supervisor, do you have the authority to disregard "Packages
Per Hour" (PPH) goals?
16) As a full-time supervisor, do you have the authority to disregard "Stops-peron-
mad-hour" (SPORR) goals?
Assigning staff/vacation/salary decisions
17) If staffing is low going into the following week, do you have the authority to
unilaterally cancel the planned vacations of your employees for the following
week?
18) If one ofyour drivers has an accident, do you have the authority to decide that
the driver does not need a ride along the next day?
19) If a driver has a minor accident, do you have the authority to instruct the
driver to ignore it and not report it?
20) Do you determine the hourly wages for the hourly employees assigned to you?
21) Do you have the authority to supervise those employees who do not work
directly under you?
22) Does the Collective Bargaining Agreement dictate how many hourly
employees can be off on vacation at any given time?
23) Does the Collective Bargaining Agreement dictate which hourly employees
get to pick vacation first?
24) Are the decisions which you make as a UPS full-time supervisor limited in
any way by the Collective Bargaining Agreement for hourly employees?
25) Do you have the authority to ignore the Collective Bargaining Agreement?
26) As a full-time hub, preload or on-road supervisor, do you have the authority to
hire more employees to your rosters without Industrial Engineering (IE) or
Human Resource (RR) approval? '.
27) As a full-time hub, preload or on-road supervisor, do you have the authority to
hire a new employee on behalf ofUPS?
Disciplining staff
28) If you see an employee violating a method, such as walking on a moving belt,
do you have the authority to iguore the behavior and allow it to continue?
29) Do other supervisors have the authority to discipline your hourly employees?
30) Do you have the authority, as a full time supervisor, to discipline the hourly
employees of another supervisor?
Working as directed
31) Are you directed by your manager or division manager to do traininglon-jobsupervision?
32) Are you required to follow UPS' methods?
33) Are you required to make sure that UPS' hourly employees are following
UPS' methods?
34) Are you required to follow UPS' methods and procedures in achieving the
goals dictated by corporate?
35) Are you required to work as directed by your manager or division manager?
36) Do you have the authority to disregard any safety method prescribed by UPS?
37) Are you required to do daily audits?
38) Do you use a checklist to perform these daily audits?
39) When you are doing a checklist audit, do you have the authority to disregard
any methods or procedures?
40) Are you required to document audits on UPS checklist or audit forms?
41) Does your manager have the final say for operational issues?
42) Does your division manager have the ultimate decision-making authority for
the facility?

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Monday, October 13, 2008

Is the bar too high for survey evidence in wage and hour cases?

In 2004 California Federal Court case, Marlo v. UPS, the court excluded the plaintiff's survey evidence in a misclassification case. The plaintiff's hired a survey firm to ask UPS employees about the duties that they performed. Based on the survey, the plaintiffs expert opined that the UPS workers were misclassified as exempt from overtime payments.

The defendant's motion questioned the reliability of the survey and the qualifications of the plaintiff's expert.

Over the next few post, we will be discussing the ins and outs of this case.

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Wednesday, September 03, 2008

Wage and hour survey discussion Part I

From the previous post (9/2/2008)According to the defense's Daubert motion, the wage and hour survey in the Big Lots case suffered from a number of flaws.

As mentioned, the court disagreed and denied the defense's motion.

List of criticisms:

* The survey responses conflicted with opt-in actual deposition testimony.

* Survey had “non-response bias and coverage error.”

* Another flaw with the survey is that it was not pretested, with the
exception of internally and with Plaintiffs’ counsel

*Recency bias, or the tendency to overweight recent experience in our perception of general experience.

* “Coverage error occurs when members of the survey population do not have an equal probability of being chosen to be part ofthe sample studied.” (Survey did not include non-opt-ins)

* Numerous survey responses that indicated confusion or dissatisfaction with survey questions. Of the 553 responses he reviewed, over 55 percent (306)contained missing or incomplete answers...

*Plaintiff expert did not provide a follow-up to questions

* Survey used the FLSA test qualifications. Focused on the long test (for exemption classification) when the short test questions were arguably the correct ones.

* Questions failed to seeks information regarding the respondent’s employment
history with BigLots. It fails to draw any distinction between time employed at Big Lots
that is at issue in thisaction and time that falls outside the statute of limitations.

*Use of the word “regularly” in the survey question resulted in a great
deal of confusion,destroying any confidence that the survey responses on the relevant
issues (hiring and firing) arereliable in terms of what is required by the regulations.

*“Regularly” is not defined in the survey instrument, leaving the respondents to formulate their own interpretations

* Term refers to average work week but does not define them.

* Some questions do not add correctly. Either their totals failed
to equal 100 percent or, as in the case of numerous respondents they listed very high percentages (between 75% to 100% foreach of the activities) evidencing total confusion about the question.

*Wrong defintion of work week. The employer defined a full time work week as 32 hours and not 40 as in the survey

* Disagreed with damage method.

Plaintiff expert calculated that, based upon the survey responses, the respondents worked anaverage of 59.3 hours per week. He further claimed, based upon a 95 percent confidenceinterval, that this means that 95 percent of all opt-ins worked 58.5 to 60 hours a week. He then concludes that all of the opt-ins should be awarded damages simplyby determining from payroll records how many weeks each Assistant Store Manager had worked, by applying theappropriate overtime factor to the base hourly rate and then multiplying the resulting overtimerate by the number of hours worked in excess of forty per week.

Sponsered Link: Looking for a survey and damages expert in a wage and hour case? Go to http://www.employstats.com/

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Tuesday, September 02, 2008

Wage and hour survey is admitted in FLSA case

John Johnson and Robert Burden v. Big Lots Stores, Inc., United States
District Court, Eastern District of Louisiana


In this case, the plaintiff's allege that the assistant store managers
are missclassifed as exempt from OT. According the plaintiff's report they
assistant managers worked on average 58 hours a week but were paid for
only 40 hours.

Plaintif's hired an ecoonomist to perform a survey of the opt-in members
of the class. The plaintiff's damage analysis was based on the survey.

Summary:

In a nutshell the defense argues that the plaintiff's survey is flawed. Argue to the brief, the flaws are as follow. First, the respondents are interested in the outcome of the litigation for
which the survey was conducted, and were told that the survey was to be used to help with their case, rendering the results unreliable. Second, additional methodological defects infected the survey with bias, rendering the analysis based upon it unreliable. Finally, the plaintiff's expert asked the wrong questions, resulting in misleading and unreliable answers.

The court disagreed and denied the defense's Daubert motion. In the coming post, we will discuss this case in more detail.

Sponsered Link: Looking for a survey and damages expert in a wage and hour case? Go to www.employstats.com

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Wednesday, July 30, 2008

Relative v. Absolute Risk employment discrimination cases

bbThe recent foreclosures in the housing market provides a very interesting example of relative versus absolute risk. The AP recently reported that 'Foreclosure filings up 121 percent from last year'. Dig a little further and it is clear that the AP is discussing relative and not absolute risk.

The story goes on and says that this year 1 out of every 171 homes is being foreclosed. This foreclosure risk number equates to approximately 0.005 or 0.5% of homes. Last year approximately 1 in 342 homes were being foreclosed or about 0.0025 or 0.25%.

Relatively speaking there was a big spike but in absolute terms, not many homes were in foreclosure.


In employment cases where statistical analysis comes into play it is also important to keep it in mind the difference between relative and absolute risk.

For instance in a wrongful termination case where there are allegations that the defendant/employer discriminated against older workers, statistical experts will typical evaluate the chance probability that a given employer would have been terminated had the employer been using a age neutral employee selection process. If the chance probability is small then it is viewed as suggestive of a discriminatory selection process.

The chance probability in an employment case that is typically a relative risk.

In other words, the chance probability measures the likelihood that one group, i.e. older workers, would have been terminated versus the likelihood that another group of workers, i.e. younger workers, would have been terminated if all factors were equal.

Accordingly, just like the case of foreclosures above, the actual number of individuals 'at risk' of being selected at any given time may be quite small. For instance, the relative risk may say that the older workers are 75% less likely to be promoted as younger workers. However in practice this relative risk of promotion may translate into an actual (absolute) gap of only 1 or 2 persons (out of many hundreds) that arguably should have been promoted. In this type of situation, a claim of class wide discrimination against older workers would be a little dubiuos to say the least.

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Monday, May 26, 2008

Statistical evidence of police racial profiling is ok

The MA Supreme Court overturned the appeallate court's exclusion of statistical evidence based on the stops made. The Supreme Judicial Court said that defendants can compare the racial composition of people stopped on a certain stretch of road with the racial composition of everyone who uses the road. (Boston Herald)

From boston.com:

Worcester District Attorney Joseph Early Jr. said the court has provided safeguards for prosecutors and defense attorneys by laying out a clear standard for showing discriminatory treatment through statistical information.

"It says that you've got to look on the highway. If a highway is passing through Grafton, Auburn, Millbury, you don't go to the towns, you find out what the racial composition of the people actually using the road is," Early

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Tuesday, April 29, 2008

What do EEO-1 reports tell you about discrimination in a hiring case?

Probably not much.

EEO-1 reports from the EEOC provide a breakdown of how many people of different racial, gender, and age groupings are hired into different job positions within a company. The detailed reports, which most times the public will not have access to, provides a breakdown by employer. The more aggregated reports, which the public generally has access to, provides a breakdown at a higher level, such as at the zip code level or higher, by industry type. So ultimately the EEO-1 reports present the composition of the employer at a given point in time, usually a year.

In contrast, in a hiring case the plaintiffs are usually alleging that the defendant failed to hire
them because of their age, race, gender or other characteristics. In these types of cases, statistical analyses that compare the individual employer’s hiring numbers to EEO-1 data are common.

However, the EEO-1 report generally makes a poor comparison.

Instead of focusing only on the employer/defendant’s hiring decisions, a firm’s EEO-1 report reflects the composition of the workforce which is the result of hiring decisions over a much longer period than are issue in the typical hiring discrimination case. In short, the composition of an employer’s workforce is not necessarily representative of the composition of the hires in any given year, or the composition of the applicants available for hire for any given year.

For example, consider a hiring case where there are allegations of age discrimination. In this example, the employer starts with a workforce of 200 employees that are under the age of 40. and zero that are 40 years of age or older. For this firm, it’s workforce composition is 0% 40 or over.

If during the following year the firm hires 20 employees and they all 40 years of age or over, the firm’s composition of older worker hires is 100%. However, the overall composition of the workforce is now just 9.09% that is 40 years of age or older. That is 20 workers who are over the age of 40 out of a total of 220 employees.

The workforce composition of 9.09% of older workers does not adequately represent that the firm’s composition of hires of 100% older workers in that year. Therefore, in this setting, the composition of the workforce is not an appropriate measure to analyze the hiring decisions in any given year.

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Wednesday, April 16, 2008

Bayesian v. Frequenist analysis of employment discrimination

In the article 'Hierarchical Models for Employment Decisions', Joseph Kadane and George Woodworth (Journal of Business and Economic Statistics, April 2004, Vol 22. No.2) advocate the use of Bayesian analysis to assist the trier of facts in the determining if the employer had discriminated against the protected groups of workers.

Conceptually, the Bayesian statistical analysis approach turns the traditional approach to analyzing statistical evidence of discrimination upside down. The traditional approach, or what statisticians refer to as the frequentist approach, begins by assuming that no discrimination has occurred and the employment decisions were made in a age, race, or gender neutral manner. From that point, the data is used to determine the likelihood that a age, race, or gender neutral employment process would have generated the employment outcomes that are at issue in the lawsuit.

In short, the frequenist approach ask:

'Assuming that the defendant is utilizing a age, gender, or race neutral employment process, what is the probability that the unbiased employment process could have generated the observed employer's employment decisions?'


If there is a very small probability that a neutral employment process would have generated the outcome then it may be inferred that discrimination has occurred.

The Bayesian approach turns the approach around and upside down The Bayesian approach ask the question:

'Given that we observe the defendant's employment decision outcomes, what is the likelihood that the employment decision was age, race or gender neutral?'

If there is a small probability that the data is consistent with a neutral employment process, then it may be inferred that some type of discrimination has occurred.

What are the pros and cons of each approach? To be discussed....!

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Monday, January 07, 2008

Court allows statistical survey evidence

(thanks Dauberttracker.com!)

In Merisant Co. vs. McNeil Nutritionals, LLC ( 4/12/2007), CIVIL ACTION NO. 04-5504, Pennsylvania, Eastern District (GENE E.K. PRATTER, United States District Judge.)

Case Summary:

Plaintiff, Merisant Company, Inc., filed a case against defendant McNeil Nutritionals, LLC, and McNeil PPC, Inc. under the Pennsylvania common law of unfair competition. The plaintiff alleged that defendant had engaged in false and misleading advertising with respect to Splenda No Calorie Sweetener.

The defendant proffered the statistical survey evidence. The plaintiff sought to exclude the survey and all related testimony and opinion.

The plaintiff argued that the defendant's survey did not meet the "fit" and "reliability" elements required by Daubert. The plaintiff further argued that the defendant's survey was neither relevant nor reliable with respect to the issues of this case. While expressing some reservations, the court nonetheless denied the motions to exclude.

This is an interesting case because the court goes into much detail and provides detailed analysis about what is required for a survey to be admissible. The court states:

In order for a survey to be admitted, its design must "fit" the issues to be decided in this case. In J&J Snack Foods Corp. v. Earthgrains Co., 220 F. Supp. 2d 358, 370 (D.N.J. 2002), the court state that: Above all, the survey's design must fit the issue which is to be decided by the jury, and not some inaccurate restatement of the issue, lest the survey findings inject confusion or inappropriate definitions into evidence, confounding rather than assisting the jury. Only if the expert testimony and related survey are useful, reliable, and have probative value after all their deficiencies are taken into account is the evidence admissible. Id. In addition, the court noted that it was "essential to consider whether the population and terms were properly defined, whether the design, questionnaires, and interviews met objective standards, whether data was accurately collected and reported, whether data was properly analyzed, whether the questions asked were unrelated to the material issues of the case, whether questions were unfairly leading, and whether questions were confusing." Id. at 369. J&J Snack Foods addressed a dispute arising in the trademark context, where a survey was submitted to show the trademark should be classified as "suggestive" instead of "generic" or "descriptive." However, the survey did not properly define any of the classifications, and, consequently, the court found that the survey had "no bearing on the issue it was submitted for." Id. at 370. The court noted that "the flawed definition permeated the entire survey to make its finding completely untrustworthy and unreliable." Id. at 370-71.

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Monday, February 12, 2007

Daubert watch: Court slams door on professor's statistical testimony

In Lucresia Mayorga Santamaria vs. Dallas Indep. Sch. Dist. ( Decided: 11/16/2006) in Federal Court in the Northen District of Texas Judge Lindsay determined that the testimony of a statistical expert would not aid or assist it in deciding whether there had been a violation of the Fourteenth Amendment or of Title VI.


This lawsuit concerned allegations of unlawful segregation of Latino school children at Preston Hollow Elementary School. Preston Hollow is an elementary school in a predominantly Anglo neighborhood in Dallas, Texas. In support of their claims, Plaintiffs offered testimony of a well known and qualified university education professor.

After conducting a mathematical analysis of the data, the stats expert concluded that the pervasive and robust within-school segregation was based on race/ethnicity. The district court determined that the professor's testimony and statistical analysis were fraught with flaws. However because the court did not feel that the professor's report would assist the court in this case, even if it were not fraught with flaws, it did not actually rule on the admissibility of the report under Fed. R. Evid. 701.

For more go to: dauberttracker.com

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Tuesday, January 16, 2007

Wage and hour focus article 1

Time and motion experts should work together with statisticians when performing time and motion studies

Case: MARIA CHAVEZ, et al., on behalf of themselves and all others similarly situated v. IBP, INC. and TYSON FOODS, INC., all Delaware corporations, Washington, Eastern District, CV-01-5093-RHW, 2005 U.S. Dist. LEXIS 29714

Punchline: Chavez v. IBP shows the importance of representativeness of a time and motion study used to measure time spent working of the clock. The plaintiffs' shadow study of time spent walking to and from job posts was disallowed and ruled to be unreliable because the study relied on non-representative walking observations

Background (from the court's order concerning the defendant's motion to decertify the class)This is a class action brought under the Fair Labor Standards Act ("FLSA"), 29 U.S.C. §§ 201-219, as well as the Washington state Minimum Wage Act ("MWA"), RCW chapter 49.46.005 et seq., the Industrial Welfare Act, RCW chapter 49.12.005 et seq., and the Wages-Deductions-Contribution-Rebate Act, RCW chapter 49.52. The Court has jurisdiction over the class members' FLSA claims under 29 U.S.C. § 216(b) and 28 U.S.C. § 1331.

The named Plaintiffs, Maria Chavez, Ranulfo Gutierrez, Paz Arroyo, Antonio Martinez, and Silverio Diaz, were employed at the Tyson beef slaughter, processing, and hides divisions in Pasco, Washington (the "Pasco Plant") sometime after November 1, 1998. The Rule 23 class was defined in the Court's certification order as: All individuals performing production work in the Pasco plant processing, slaughter and hides division during any time between November 2, 1998 through May 14, 2002, excluding supervisors, managers, quality control employees, guards, mechanics, laundry room employees, janitors, knife room employees, and packaging department employees whose jobs are limited to work performed after the product has been bagged and boxed.

The class is comprised of 1,136 opt-in Plaintiffs bringing claims under the FLSA and Washington state law, and 3,909 Rule 23 Plaintiffs (including 116 FLSA opt-in Plaintiffs with state and federal claims and 2,797 Rule 23 Plaintiffs with only Washington state claims) (Ct. Rec. 633). At trial, 36 processing class members, 14 slaughter class members, and 3 hides class members testified. In total, approximately 5% of the opt-in class, and less than 1% of the opt-out class, testified. The class Plaintiffs seek damages for uncompensated work performed during the period commencing on November 2, 1998, and ending on December 31, 2003.

Expert's part and court opinion of time and motion expert's work:

In a previous case (Alvarez), Plaintiffs presented the testimony of Dr. Kenneth Mericle on the issue of amount of time employees spend walking from their lockers to the production room floor. Dr. Mericle calculated the Alvarez walking times by utilizing a standard rate of speed developed by industrial engineers. In the present action, Plaintiffs assert that the Alvarez walking calculations vastly underestimate the time actually spent walking, and present alternative times based on Dr. Mericle's shadowing study. Dr. Mericle concludes that the average pre-shift walking times for Slaughter are 1.822 minutes and for Processing are 2.622 minutes (Id.). These times include "walking segments from the locker, to the workstation and includes walking to clean glasses and obtain knives, sand paper and miscellaneous job related equipment but not walking for gloves." (Id.)

The Court finds that Dr. Mericle's new walking calculations include instances where employees unnecessarily backtracked or retraced their steps; therefore, they are not an accurate representation of walk time that is work. In addition, Dr. Mericle's walking calculation included a significant amount of walking to complete job activities that were unique to certain job categories. Therefore, the Court finds that Dr. Mericle's calculations did not provide representative evidence of the walking time expended by the class as a whole.

What could have been done: A more representative sample of walking observations could have yielded a more scientifically valid study and may have not been subject to the the same criticisms.

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Tuesday, January 09, 2007

Judge says: Let them both in!

In a N.J. employment discrimination case, Judge William Walls, faced with dueling stats experts found both of the cases to be admissible.

Background and case from www.dauberttracker.com

The plaintiffs were former and current employees of the defendants Johnson & Johnson. The plaintiff filed an employment discrimination suit on behalf of themselves and other similarly situated employees against Johnson & Johnson. The case was filed pursuant to Section 1981 of the Civil Rights Act of 1871, as amended by the Civil Rights Act of 1991, and the New Jersey Law Against Discrimination, N.J. Stat. ¤ 10:5-1.

The expert statistical report, prepared by Dr. Janice Madden and Dr. Alexander Vekker ("Madden Report"), was relied upon by the plaintiff to support their claim of commonality. Defendant filed a motion to strike the Madden Report arguing that (1) the Madden Report was irrelevant to class certification and therefore "unfit" under Daubert and (2) the Madden Report was unreliable.

The Madden Report concluded that from 1997 to 2003: (1) African American employees were less likely than comparably qualified white employees to be selected for promotion, (2) African Americans and Hispanics had lower base salaries than comparably qualified whites, and (3) there was an average wage differential at hire by race and ethnicity. The court rejected defendant's motion to preclude the Madden Report in light of the fact that the Madden Report controlled for job hierarchy, job function, age, tenure at Johnson & Johnson, and education.

The court held that Dr. Madden's regressions were not so incomplete that they were unreliable or irrelevant.

The Defendant submitted the Wise Report prepared by Dr. David Wise, an expert on statistical data, to support its contention that the Johnson & Johnson companies were not a single class environment for the purpose of class certification. The Wise Report concluded: (1) there was no common pattern of compensation and promotion consistently adverse to African American and Hispanic employees, (2) the data were inconsistent with the assumption that the determinants of compensation and promotion were the same at all Johnson & Johnson companies, (3) few of the estimated minority effects were statistically different than zero, and (4) to the extent that there were differences in compensation and promotion, they were small and could be explained by small differences between the job-related attributes of minority and white employees.

The court denied plaintiff's motion to strike the expert report as it concluded that the report was not so fatally flawed as to be inadmissible as a matter of law.

Therefore, the court denied both the plaintiff and defendant's motion to strike each other's expert

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Friday, December 01, 2006

Importance of statistical sampling in legal cases

While courts are becoming more and more accepting of the random sampling techniques in many types of cases, there is still the concern the use of random sampling violates a defendant's right to due process. For instance, in the Republic Servs. vs. Liberty Mut. Ins. Co. case discussed a few days ago in our blog, the court took note of the defendant's argument, but ruled that statistical sampling was useful and allowed it.

Other judges in other cases have ruled, from the bench, that the law simply does not provide for sampling regardless of its accuracy or cost savings.

A post on a listserv, shows a funny exchange between a MD and attorney concerning the use of sampling:

Q. Dr., would you agree that it is always better to make a complete study rather than take a sample?

A. Well, if you ever come to me for a physical, I will be sure to take all of your blood rather than just a sample.

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Wednesday, November 29, 2006

Stats experts live to analyze another day...

On 10/3/2006 in Holster vs. McMaster-Carr Supply Co., Judge Garret Brown ok's plaintiff's statistical analysis of termination data in a RIF action.

In Republic Servs. vs. Liberty Mut. Ins. Co., Judge finds the use of statistical sampling of workers compensation claim files to assess defendant's liability and damages is valid and does not violate the defendant's rights. (10/2/2006)

Go to dauberttracker.com to learn more...

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