Disability Statistics and Demographics Rehabilitation Research and Training Center

Disability Statistics and Demographics Rehabilitation and Research Training Center graphic for decoration only

Bridging the Divide

High quality disability statistics play an important role in efforts to address disparities between people with and without disabilities. However, there is a divide between the producers and end users of disability statistics. Producers face challenges with the complexity of representing disability with data collection instruments and removing barriers for people with disabilities to participate in data collection efforts . On the other hand, end users often struggle to understand the different definitions of disability bein used in data sources. Also, the fragmented production of disability statistics across several agencies makes statistics difficult to find, interpret, and compare. The Disability Statistics and Demographics RRTC actively narrows and bridges the divide between the producers and end users of disability statistics by conducting comprehensive and integrated research and knowledge translation activities, ultimately aiming to improve conditions for people with disabilities and their families.



Kessler Foundation
Association of University Centers on Disabilities

The StatsRRTC is funded by a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number 90RTGE0005). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). The contents of this website do not necessarily represent the policy of NIDILRR, ACL, or HHS, and you should not assume endorsement by the Federal Government.

  • Comparing Leading Disability Question Sets

    • Project lead – Andrew Houtenville, University of New Hampshire
    • This project assesses whether differences in two disability question sets commonly included in disability research—the American Community Survey (ACS) and Washington Group Short (WGS) question sets—influence outcome estimates, with particular attention paid to disability severity, which is a frequently-missing dimension in disability statistics. 
  • New Survey Items to Measure Barriers

    • Project lead – Kimberly Phillips, University of New Hampshire
    • This project develops new survey items to identify barriers people with disabilities face in discrete activities related to their employment, health care, transportation and housing. The aim is to generate more actionable information to help address or reduce barriers to community participation. 
  • Data Collection Operations

    • Project lead – David Mann, Mathematica
    • This project examines differences in respondents’ propensity to complete two kinds of electronically-delivered surveys to determine the extent to which samples of people with disabilities recruited using web surveys correspond to the population from which they are drawn.
  • Geographic Variation in the Disablement Process

    • Project lead – Andrew Houtenville, University of New Hampshire
    • This project generates new knowledge about the geographic variation in disability and new local-level statistics, based on the social model of disability.
  • New State-Level Statistics

    • Project lead – Yonatan Ben-Shalom, Mathematica
    • This project produces new state-level statistics on the social and economic outcomes of people with disabilities that are not available in other publications, primarily because of limitations in sample sizes.
  • New and Expanded Details on Outcomes of People with Disabilities

    • Project lead – Debra Brucker, University of New Hampshire
    • This project investigates new details about disparities in health, economic, and social outcomes related to pressing policy needs through a series of one-year projects.
  • SSA Beneficiary Characteristics 

    • Project lead – Gina Livermore, Mathematica
    • This project uses new survey data alongside existing administrative data to examine the work behavior of SSI and SSDI beneficiaries.
  • Data Analytics for VR Program Administration

    • Project lead – David Mann, Mathematica
    • This project leverages new and underutilized administrative data tools to investigate VR program operations to inform program improvement. Specifically, it uses both traditional econometric and newer data science methods to build predictive models of VR progression.
  • Disaster Preparedness and Disability

    • Project lead – Purvi Sevak, Mathematica
    • This project documents and analyzes county-specific data influencing disaster response capacity for residents with disabilities. This data will be made publicly available to assist policy discussions and identify regions where there are unmet disaster preparedness needs for people with disabilities.
  • Data Analytics for Health Surveillance

    • Project lead – Kimberly Phillips, University of New Hampshire
    • This project uses “all-payer” health insurance claims data to investigate health outcomes and health care utilization of people with specific disabilities, paying attention to differences between Medicaid and private insurance claims.
  • Annual Report on People with Disabilities in the US

    • Project lead – Andrew Houtenville, University of New Hampshire
    • This project produces statistics on the current status and trends of people with disabilities in the US, including topics related to employment, health, community living, and other outcomes of current importance.
  • Disability Compendium, Supplement, and State Reports

    • Project lead – Andrew Houtenville, University of New Hampshire
    • The Disability Compendium is updated, disseminated, and expanded each year, offering a comprehensive set of disability statistics from a wide variety of sources on a vast number of topics, at the national, state, and (when possible) local levels. 
  • Compendium of Survey Methods

    • Project lead – Jason Markesich, Mathematica
    • This project annually updates and publishes the Compendium of Survey Methods, which is an indexed, annotated bibliography. Each entry contains the citation, abstract, and a summary of key findings and points of interest.
  • Annual Infographics on Key Demographics

    • Project lead – Kimberly Phillips, University of New Hampshire
    • This project produces and disseminates annually-updated infographics that focus on the intersection of disability with other key socio-demographics. 
  • Disability Statistics Self/Independent Study Curriculum 

    • Project lead – Andrew Houtenville, University of New Hampshire
    • This project creates a Disability Statistics Curriculum for self/independent study that provides resources for students, professors, and other individuals looking to learn how to access and analyze data related to people with disabilities.