Measurement precision and efficiency of multidimensional computer adaptive testing of physical functioning using the pediatric evaluation of disability inventory

Arch Phys Med Rehabil. 2006 Sep;87(9):1223-9. doi: 10.1016/j.apmr.2006.05.018.

Abstract

Objective: To compare the measurement efficiency and precision of a multidimensional computer adaptive testing (M-CAT) application to a unidimensional CAT (U-CAT) comparison using item bank data from 2 of the functional skills scales of the Pediatric Evaluation of Disability Inventory (PEDI).

Design: Using existing PEDI mobility and self-care item banks, we compared the stability of item calibrations and model fit between unidimensional and multidimensional Rasch models and compared the efficiency and precision of the U-CAT- and M-CAT-simulated assessments to a random draw of items.

Setting: Pediatric rehabilitation hospital and clinics.

Participants: Clinical and normative samples.

Interventions: Not applicable.

Main outcome measures: Not applicable.

Results: The M-CAT had greater levels of precision and efficiency than the separate mobility and self-care U-CAT versions when using a similar number of items for each PEDI subdomain. Equivalent estimation of mobility and self-care scores can be achieved with a 25% to 40% item reduction with the M-CAT compared with the U-CAT.

Conclusions: M-CAT applications appear to have both precision and efficiency advantages compared with separate U-CAT assessments when content subdomains have a high correlation. Practitioners may also realize interpretive advantages of reporting test score information for each subdomain when separate clinical inferences are desired.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Child
  • Child, Preschool
  • Computers
  • Disability Evaluation*
  • Disabled Persons / classification*
  • Disabled Persons / rehabilitation
  • Efficiency
  • Humans
  • Infant
  • Outcome Assessment, Health Care
  • Pediatrics*
  • Psychometrics
  • Self Care