In this monograph we examine the added value of new psychometric methods (Rasch measurement and Item Response Theory) over traditional psychometric approaches by comparing and contrasting their psychometric evaluations of existing sets of rating scale data. We have concentrated on Rasch measurement rather than Item Response Theory because we believe that it is the more advantageous method for health measurement from a conceptual, theoretical and practical perspective. Our intention is to provide an authoritative document that describes the principles of Rasch measurement and the practice of Rasch analysis in a clear, detailed, non-technical form that is accurate and accessible to clinicians and researchers in health measurement.

A comparison was undertaken of traditional and new psychometric methods in five large sets of rating scale data: (1) evaluation of the Rivermead Mobility Index (RMI) in data from 666 participants in the Cannabis in Multiple Sclerosis (CAMS) study; (2) evaluation of the Multiple Sclerosis Impact Scale (MSIS-29) in data from 1725 people with multiple sclerosis; (3) evaluation of test-retest reliability of MSIS-29 in data from 150 people with multiple sclerosis; (4) examination of the use of Rasch analysis to equate scales purporting to measure the same health construct in 585 people with multiple sclerosis; and (5) comparison of relative responsiveness of the Barthel Index and Functional Independence Measure in data from 1400 people undergoing neurorehabilitation.

Both Rasch measurement and Item Response Theory are conceptually and theoretically superior to traditional psychometric methods. Findings from each of the five studies show that Rasch analysis is empirically superior to traditional psychometric methods for evaluating rating scales, developing rating scales, analysing rating scale data, understanding and measuring stability and change, and understanding the health constructs we seek to quantify.

There is considerable added value in using Rasch analysis rather than traditional psychometric methods in health measurement. Future research directions include the need to reproduce our findings in a range of clinical populations, detailed head-to-head comparisons of Rasch analysis and Item Response Theory, and the application of Rasch analysis to clinical practice.

In this monograph we examine the added value of new psychometric methods (Rasch measurement and Item Response Theory) over traditional psychometric approaches by comparing and contrasting their psychometric evaluations of existing sets of rating scale data. We have concentrated on Rasch measurement rather than Item Response Theory because we believe that it is the more advantageous method for health measurement from a conceptual, theoretical and practical perspective. Our intention is to provide an authoritative document that describes the principles of Rasch measurement and the practice of Rasch analysis in a clear, detailed, non-technical form that is accurate and accessible to clinicians and researchers in health measurement.

A comparison was undertaken of traditional and new psychometric methods in five large sets of rating scale data: (1) evaluation of the Rivermead Mobility Index (RMI) in data from 666 participants in the Cannabis in Multiple Sclerosis (CAMS) study; (2) evaluation of the Multiple Sclerosis Impact Scale (MSIS-29) in data from 1725 people with multiple sclerosis; (3) evaluation of test-retest reliability of MSIS-29 in data from 150 people with multiple sclerosis; (4) examination of the use of Rasch analysis to equate scales purporting to measure the same health construct in 585 people with multiple sclerosis; and (5) comparison of relative responsiveness of the Barthel Index and Functional Independence Measure in data from 1400 people undergoing neurorehabilitation.

Both Rasch measurement and Item Response Theory are conceptually and theoretically superior to traditional psychometric methods. Findings from each of the five studies show that Rasch analysis is empirically superior to traditional psychometric methods for evaluating rating scales, developing rating scales, analysing rating scale data, understanding and measuring stability and change, and understanding the health constructs we seek to quantify.

There is considerable added value in using Rasch analysis rather than traditional psychometric methods in health measurement. Future research directions include the need to reproduce our findings in a range of clinical populations, detailed head-to-head comparisons of Rasch analysis and Item Response Theory, and the application of Rasch analysis to clinical practice.