Health Outcomes Methodology: Symposium ProceedingsItem Response Theory and Health Outcomes Measurement in the 21st CenturyHays, Ron D. PhD*†; Morales, Leo S. MD, MPH*†; Reise, Steve P. PhD*‡ Author Information *From UCLA, School of Medicine, Los Angeles, California. †From UCLA, Department of Psychology, Los Angeles, California. ‡From RAND, Health Sciences, Santa Monica, California. Address correspondence and requests for reprints to: Ron D. Hays, PhD, Division of General Internal Medicine and Health Services Research, 911 Broxton Plaza, Room 110, Box 951736, Los Angeles, CA 90095-1736. E-Mail: [email protected] Medical Care 38(9):p II-28-II-42, September 2000. Buy Abstract Item response theory (IRT) has a number of potential advantages over classical test theory in assessing self-reported health outcomes. IRT models yield invariant item and latent trait estimates (within a linear transformation), standard errors conditional on trait level, and trait estimates anchored to item content. IRT also facilitates evaluation of differential item functioning, inclusion of items with different response formats in the same scale, and assessment of person fit and is ideally suited for implementing computer adaptive testing. Finally, IRT methods can be helpful in developing better health outcome measures and in assessing change over time. These issues are reviewed, along with a discussion of some of the methodological and practical challenges in applying IRT methods. © 2000 Lippincott Williams & Wilkins, Inc.