Equating health status measures with item response theory: illustrations with functional status items

Med Care. 2000 Sep;38(9 Suppl):II43-59. doi: 10.1097/00005650-200009002-00008.


Background: More than 75 instruments have been developed to measure functional status. These measures differ in number of items, type of rating scale, and item difficulty. Such variations render it impossible to compare data across different measures. One way to overcome such test dependency is test equating, which relates scores from different measures to a common metric.

Objective: We developed a bank of physical functioning items and equated them using item response theory.

Design: We used a common-item equating design and a self-administered survey of functional status.

Subjects: Individuals > or = 65 years of age who had > or = 1 ambulatory visit across a 3-month sampling frame to a Veterans Administration Medical Center or its affiliated university medical center.

Results: The dressing items were the most discriminating, followed by bathing, toileting, mobility, cooking/eating, and household and community activities. The 5 most discriminating items were to put underclothes on, manage clothes after toileting, move between rooms, take pants/slacks off, and get into bed. Most of the items were located on the easier end of the ability continuum. Only 6 would classify as being very difficult.

Conclusions: We used item response theory to equate and calibrate a large number of activities of daily living on the same scale; by doing so, we were able to better understand the structure and order of domain-specific items to each other, as well as the interrelations among items across the ability continuum.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Activities of Daily Living*
  • Aged
  • Aged, 80 and over
  • Ambulatory Care / statistics & numerical data
  • Geriatric Assessment / classification*
  • Health Services Research / methods
  • Health Status Indicators*
  • Hospitals, Veterans / statistics & numerical data
  • Humans
  • Models, Statistical*
  • Wisconsin