Practical implications of item response theory and computerized adaptive testing: a brief summary of ongoing studies of widely used headache impact scales.

We have the potential to substantially advance the field of health status assessment by constructing and calibrating questionnaires based on item response theory (IRT) and administering them using computerized adaptive methods. This opportunity could hardly come at a better time. The health care industry needs more practical tools to monitor population health on a large scale as well as more precise tools to identify those who need and are most likely to benefit from treatment. Furthermore, we need to standardize the concepts and metrics of health sufficiently to permit comparisons of results across assessment tools and across diverse applications. To achieve the full potential of IRT models, many methodological issues must be addressed, including those raised by Hays et al1 and McHorney and Cohen.2 In responding to these authors, we have chosen to emphasize the practical implications of IRT models, particularly their usefulness for purposes of computerized adaptive health assessments. We briefly summarize ongoing efforts to calibrate and dynamically administer widely used measures of headache impact, note similarities and differences in our analytic approaches, and comment on the implications of IRT methodology.

[1]  William Meredith,et al.  Notes on factorial invariance , 1964 .

[2]  M. R. Novick,et al.  Statistical Theories of Mental Test Scores. , 1971 .

[3]  B. Muthén.  Contributions to factor analysis of dichotomous variables , 1978 .

[4]  Georg Rasch,et al.  Probabilistic Models for Some Intelligence and Attainment Tests , 1981, The SAGE Encyclopedia of Research Design.

[5]  G. Masters.  A rasch model for partial credit scoring , 1982 .

[6]  B. Muthén.  A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators , 1984 .

[7]  David Thissen,et al.  A taxonomy of item response models , 1986 .

[8]  J. Ramsay.  Kernel smoothing approaches to nonparametric item characteristic curve estimation , 1991 .

[9]  Fritz Drasgow,et al.  Distinguishing Among Paranletric item Response Models for Polychotomous Ordered Data , 1994 .

[10]  J E Ware,et al.  The status of health assessment 1994. , 1995, Annual review of public health.

[11]  Ivo W. Molenaar,et al.  Estimation of Item Parameters , 1995 .

[12]  I. W. Molenaar,et al.  Rasch models: foundations, recent developments and applications , 1995 .

[13]  N. Ramadan,et al.  Headache Disability Inventory (HDI): Short‐term Test‐Retest Reliability and Spouse Perceptions , 1995, Headache.

[14]  R. Lipton,et al.  Variation in migraine prevalence by race , 1996, Neurology.

[15]  E. Muraki.  A Generalized Partial Credit Model , 1997 .

[16]  R. J. Mokken,et al.  Handbook of modern item response theory , 1997 .

[17]  W. Fisher,et al.  Equating the MOS SF36 and the LSU HSI Physical Functioning Scales. , 1997, Journal of outcome measurement.

[18]  P. Jhingran,et al.  Development and Validation of the Migraine‐Specific Quality of Life Questionnaire , 1998, Headache.

[19]  Anastasia E. Raczek,et al.  Comparison of Rasch and summated rating scales constructed from SF-36 physical functioning items in seven countries: results from the IQOLA Project. International Quality of Life Assessment. , 1998, Journal of clinical epidemiology.

[20]  Beth A. Reboussin,et al.  An estimating equations approach for the LISCOMP model , 1998 .

[21]  R. Lipton,et al.  Reliability of the Migraine Disability Assessment Score in A Population-Based Sample of Headache Sufferers , 1999, Cephalalgia : an international journal of headache.

[22]  R. Lipton,et al.  Validity of an illness severity measure for headache in a population sample of migraine sufferers , 1999, PAIN.

[23]  C. McHorney,et al.  Equating Health Status Measures With Item Response Theory: Illustrations With Functional Status Items , 2000, Medical care.

[24]  RON D. HAYS,et al.  Item Response Theory and Health Outcomes Measurement in the 21st Century , 2000, Medical care.

[25]  Howard Wainer,et al.  Computerized Adaptive Testing: A Primer , 2000 .

[26]  D. Cella,et al.  Response to Hays et al and McHorney and Cohen: A Discussion of Item Response Theory and Its Applications in Health Status Assessment , 2000, Medical care.