Hobart J, Cano S
Neurological Outcome Measures Unit, Department of Clinical Neurosciences, Peninsula College of Medicine and Dentistry, Plymouth, UK.
Health Technol Assess. 2009 Feb;13(12):iii, ix-x, 1-177. doi: 10.3310/hta13120.
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.
在本专著中，我们通过比较和对比新的心理测量方法（拉施测量法和项目反应理论）与传统心理测量方法对现有评定量表数据集的心理测量评估，来研究新方法的附加值。我们专注于拉施测量法而非项目反应理论，因为我们认为从概念、理论和实践角度来看，它是健康测量中更具优势的方法。我们的目的是提供一份权威文件，以清晰、详细、非技术性的形式描述拉施测量法的原理和拉施分析的实践，供健康测量领域的临床医生和研究人员准确理解和使用。
对五组大型评定量表数据进行了传统心理测量方法与新心理测量方法的比较：（1）对来自666名参与多发性硬化症大麻研究（CAMS）的参与者的数据进行里弗米德运动指数（RMI）评估；（2）对来自1725名多发性硬化症患者的数据进行多发性硬化症影响量表（MSIS - 29）评估；（3）对来自150名多发性硬化症患者的数据进行MSIS - 29的重测信度评估；（4）对585名多发性硬化症患者中用于测量相同健康结构的量表进行拉施分析等效性检验；（5）对1400名接受神经康复治疗的患者的数据进行巴氏指数和功能独立性测量的相对反应性比较。
拉施测量法和项目反应理论在概念和理论上均优于传统心理测量方法。五项研究中的每项研究结果均表明，在评估评定量表、开发评定量表、分析评定量表数据、理解和测量稳定性及变化，以及理解我们试图量化的健康结构方面，拉施分析在实证上优于传统心理测量方法。
在健康测量中，使用拉施分析而非传统心理测量方法具有相当大的附加值。未来的研究方向包括需要在一系列临床人群中重现我们的研究结果，对拉施分析和项目反应理论进行详细的直接比较，以及将拉施分析应用于临床实践。
