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Erschienen in: Quality of Life Research 9/2008

01.11.2008

Deriving utility scores from the SF-36 health instrument using Rasch analysis

verfasst von: Graeme Hawthorne, Konstancja Densley, Julie F. Pallant, Duncan Mortimer, Leonie Segal

Erschienen in: Quality of Life Research | Ausgabe 9/2008

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Abstract

Background

Utility scores for use in cost-utility analysis may be imputed from the SF-36 health instrument using various techniques, typically regression analysis. This paper explored imputation using partial credit Rasch analysis.

Method

Data from the Assessment of Quality of Life (AQoL) instrument validation study were re-analysed (n = 996 inpatients, outpatients and a community sample). For each AQoL item, factor analysis identified those SF-36 items forming a unidimensional scale. Rasch analysis located scale logit scores for these SF-36 items. The logit scores were used to assign AQoL item scores. The standard AQoL scoring algorithm was then applied to obtain the utility scores.

Results

Many SF-36 items were limited predictors of AQoL items; some items from both instruments obtained disordered thresholds. All imputed scores were consistent with the AQoL model and fell within AQoL score boundaries. The explained variance between imputed and true AQoL scores was 61%.

Discussion

Rasch-imputed mapping, unlike many regression-based algorithms, produced results consistent with the axioms of utility measurement, while the proportion of explained variance was similar to regression-based modelling. Item properties on both instruments implied that some items should be revised using Rasch analysis. The methods and results may be used by researchers needing to impute utility scores from SF-36 health scores.
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Metadaten
Titel
Deriving utility scores from the SF-36 health instrument using Rasch analysis
verfasst von
Graeme Hawthorne
Konstancja Densley
Julie F. Pallant
Duncan Mortimer
Leonie Segal
Publikationsdatum
01.11.2008
Verlag
Springer Netherlands
Erschienen in
Quality of Life Research / Ausgabe 9/2008
Print ISSN: 0962-9343
Elektronische ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-008-9395-5

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