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Center for Large Data Research & Data Sharing in Rehabilitation (CLDR)

New research tools for exploring disability, rehabilitation-related national-survey and administrative claims data

Finding Disability and Rehabilitation Related Data: What's in it for You?
Tools for locating national-survey and administrative data
June 22, 2016, 2:00 - 3:00 PM EDT

Secondary datasets such as national surveys and administrative data are valuable resources for testing hypotheses and generating national-level statistics about disability and rehabilitation related-issues. Unfortunately, it can be difficult to identify what datasets are available and what data are most appropriate for addressing a specific research interest.

This presentation will introduce two innovative web-based resources designed to help researchers learn:

  • What datasets related to disability and rehabilitation are out there?
  • What topics are covered in each dataset?
  • What are the dataset strengths and limitations?
  • How do I access the datasets?

Presenters:

  • Bill Erickson, M.S., Research Specialist, Yang Tan Institute on Employment and Disability
  • Sarah von Schrader, PhD., Research Associate, Yang Tan Institute on Employment and Disability

Ask Our Researchers

Have a question about rehabilitation datasets? Contact our researchers for technical assistance, log in or register.

The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

Other CLDR supported resources and collaborative opportunities:

Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

For questions or comments please contact disabilitystatistics@cornell.edu

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