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Combining Rasch and cluster analysis: a novel method for developing rheumatoid arthritis states for use in valuation studies

Listed author(s):
  • McTaggart-Cowan, H
  • Brazier, J
  • Tsuchiya, A

Purpose: Health states that describe an investigated condition are a crucial component of valuation studies. The health states need to be distinct, comprehensible, and data-driven. The objective of this study was to describe a novel application of Rasch and cluster analyses in the development of three rheumatoid arthritis health states. Methods: The Stanford Health Assessment Questionnaire (HAQ) was subjected to Rasch analysis to select the items that best represent disability. K-means cluster analysis produced health states with the levels of the selected items. The pain and discomfort domain from the EuroQol-5D was incorporated at the final stage. Results: The results demonstrate a methodology for reducing a dataset containing individual disease-specific scores to generate health states. The four selected HAQ items were bending down, climbing steps, lifting a cup to your mouth, and standing up from a chair. Conclusions: Overall, the combined use of Rasch and cluster analysis has proved to be an effective technique for identifying the most important items and levels for the construction of health states.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 29834.

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Date of creation: 2008
Handle: RePEc:pra:mprapa:29834
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  1. Brooks, Richard AU -, 1996. "EuroQol: the current state of play," Health Policy, Elsevier, vol. 37(1), pages 53-72, July.
  2. Young, Tracey A. & Yang, Y & Brazier, J & Tsuchiya, A, 2007. "The use of Rasch analysis as a tool in the construction of a preference based measure: the case of AQLQ," MPRA Paper 29802, University Library of Munich, Germany.
  3. Young, Tracey A. & Yang, Y & Brazier, J & Tsuchiya, A & Coyne, K, 2008. "Making Rasch decisions: the use of Rasch analysis in the construction of preference based health related quality of life instruments," MPRA Paper 29828, University Library of Munich, Germany.
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