---
title: "Court Excludes Data Analysis Expert Witness’ Opinions on the Issue of Fair Housing"
meta:
  "og:description": "Data analysis expert witness failed to consider any extraneous variables that might have explained the lack of families with children choosing to live at Defendants' properties"
  "og:title": "Court Excludes Data Analysis Expert Witness’ Opinions on the Issue of Fair Housing"
  author: "Expert Witness Profiler"
  description: "Data analysis expert witness failed to consider any extraneous variables that might have explained the lack of families with children choosing to live at Defendants' properties"
---

# Court Excludes Data Analysis Expert Witness’ Opinions on the Issue of Fair Housing

Posted on February 7, 2025 by Expert Witness Profiler

Plaintiff, the Fair Housing Center of Central Indiana (“FHCCI”) sued Defendants, M&J Management Company, LLC, d/b/a The Sexton Companies, Sexton Carlyle, LLC, Remington Court, LLC, and Sexton Windsor, LLC (collectively, the “Defendants” or “M&J Management”) based solely on Defendants’ occupancy policy requiring no more than two occupants per bedroom (“Defendants’ Occupancy Standard”).

FHCCI claimed Defendants’ Occupancy Standard discriminates based on familial status in violation of the federal Fair Housing Act (“FHA”), and the Indiana Fair Housing Act (“IFHA”), by creating a disparate impact.

The Fair Housing Center of Central Indiana is a private, non-profit Indiana corporation headquartered in Indianapolis that provides fair housing services throughout the state. Plaintiff’s mission is to ensure and enhance equal housing opportunities by eliminating housing discrimination through advocacy, enforcement, education, and outreach. Plaintiff receives 1,650 to 1,800 complaints and inquiries per year from the public, though typically only 30-40 complaints per year relate to minor children.

Plaintiff hired [James Colbert](https://expertwitnessprofiler.com/expert-witness/James-Colbert/1560739) to tabulate census data and analyze whether Defendants’ occupancy standard has a disproportionate effect on households with minor children. Colbert is a data manager and analyst for the Polis Center. 

Defendants argued that Colbert lacked proper training and qualifications to render an opinion regarding causation in a fair housing case, his report consisted of unsupported factual and legal conclusions, and his testimony was unreliable and unhelpful.

When the Defendants initially filed a motion to preclude Colbert, the Court recognized their concerns, agreed that the value of Colbert’s testimony was uncertain, but nevertheless denied the motion. Subsequently, Defendants renewed their motion to strike Colbert.

## **Data Analysis Expert Witness**

[James Colbert](https://expertwitnessprofiler.com/expert-witness/James-Colbert/1560739) has been employed by the Polis Center since February of 2004 in one capacity or another, including as a student intern, full timeemployee and contractor.

During the last 19 years he has worked with many data sets including Census data. His experience with Census data includes collection of published data, analysis, transformation, and dissemination.

[Get the full story on challenges to James Colbert’s expert opinions and testimony with an in-depth Challenge Study.](https://app.expertwitnessprofiler.com/login?eId=1560739) 

## **Discussion by the Court**

#### **_James Colbert_**

To perform his analysis, Colbert used the American Community Survey (ACS) Public Use Microdata Samples (PUMS). The ACS data is collected from a data sample of about 1% of the U.S. population through a yearly survey collected by the U.S. Census using questionnaires. PUMS data is public microdata that looks at individual-level responses to the ACS.

When reviewing PUMS data, an analyzer can only review data from the state level or from a Public Use Microdata Area (PUMA), which is an area that contains at least 100,000 people. PUMS data only accounts for a limited number of variables for data collected from households: tenure (owned or rented), number of people in households, age of occupants, rents, and rent adjustment variables. There are no variables for square footage of the household, type of household (apartment or house), amenities, public transportation, or a tenant’s preference. The surveys rely on self-reported data, so the data is only accurate if the respondent answered accurately. 

He examined data from 2017 to 2021. Colbert considered whether rental households with minor children would be disproportionally affected by a landlord’s occupancy standard of two persons per bedroom by calculating a “risk for disparity ratio.” He concluded that for the three apartment complexes in question, the percentage of children living at the apartments are lower than the percentage of children living in rental households in larger geographies in which the complexes are contained. 

### **Analysis**

To establish a _prima facie_ case of disparate impact, Plaintiff must first identify an outwardly neutral policy and compare how that policy affects a protected class compared with others.

Defendants’ occupancy standard is an outwardly neutral policy that impacts a protected class, because it excludes households with three or more minor children from renting at Defendants’ apartment complexes. However, Plaintiff’s _prima facie_ case must go one step further and demonstrate the essential element of robust causality. 

Plaintiff claimed that because households with more occupants tend to include families with minor children, and Defendants do not have a high percentage of families with children residing at the apartments in question, then Defendants’ occupancy standard must cause the low percentage of families with children, and there can be no other explanation.

The Court held that Plaintiff failed to demonstrate robust causality. Plaintiff largely relied on testimony from its expert, James Colbert. 

#### **Qualification**

The Court held that Colbert is not qualified to give opinion on the issue of fair housing. He is not a statistician or an expert in statistics, and he has no specific training or work experience on housing, occupancy standards, fair housing, housing discrimination, housing laws, or managing and owning multifamily housing. Colbert and Plaintiff failed to explain how Colbert’s experience in data management leads to his conclusion that Defendants’ occupancy standard had a disparate impact on families with children, why his experience is a sufficient basis for the opinion, or how Colbert’s experience reliably applied to the facts. Colbert had no education related to PUMS data, no experience collecting ACS or PUMA data, and no involvement in the compilation of the data he used to form his opinion.

Even if the Court found Colbert qualified to give an opinion, his opinions were excluded because his methodology is not based on sufficient facts and data. Colbert admitted his techniques were never subject to peer review or publication. Neither Plaintiff nor Colbert presented evidence related to the known potential rate of error to Colbert’s techniques.

#### **Methodology**

When making his findings, Colbert only considered four variables: whether someone rented or owned, the age of occupants, rent, and rent adjustment variables. Colbert never looked at floor plans of Defendants’ properties, and he knew nothing about their square footage. The Court found that Colbert failed to consider any extraneous variables or potential key relevant factors that might have explained the lack of families with children choosing to live at Defendants’ properties, such as less square footage, small appliances, school districts, or parking.

Colbert did not compile the PUMS or ACS data he relies on, so he could not account for its veracity. In addition, when comparing this data with Defendants’ properties, Colbert relied on a snapshot in time: tenant rosters for the properties at issue on August 9, 2022. Tenants renting apartments change daily, and without any further data points, it is impossible to know if the data he relied on was consistent with any point in time beyond that moment on August 9.

The Court held that the analytical gaps between the data and Colbert’s conclusions are too great. Colbert’s methodology is not limited to prospective tenants or actual applicants. Rather, his analysis assumes all families with children who currently rent (in any type of housing) want to live at Defendants’ apartments but were excluded from doing so, which resulted in a disparate impact on many families with children. However, Colbert’s methodology resulted in a skewed result, as it is not clear what number of families captured actually desired to live at Defendants’ apartments. Colbert failed to consider any alternative causal variables.

The Court held that the Plaintiff must present reliable evidence showing that the Defendants’ occupancy policy caused a disparity, but they failed to do so. Colbert explicitly stated that he was not opining on causation.

## **Held**

The Court granted Defendants’ renewed motion to exclude Plaintiff’s expert James Colbert. Even if his testimony were allowed, it would not be sufficient to establish a _prima facie_ case of disparate impact under the FHA or IFHA.

## **Key Takeaway:**

It was noted that Colbert’s theory and techniques were never subjected to peer review or publication. Colbert had no knowledge as to whether occupancy increasing results in increased vermin, increased wear and tear, or faster devaluation of property. In conclusion, Colbert did not have an opinion on whether Defendants’ policies caused a discriminatory effect. 

Please refer to the blog previously published about this case:

[Data Analysis Expert Witness’ Testimony Admitted Despite his Failure to Incorporate Extraneous Factors in his Analysis](https://expertwitnessprofiler.com/data-analysis-expert-witness-testimony-admitted-despite-his-failure-to-incorporate-extraneous-factors-in-his-analysis)

## **Case Details:**

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