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Quality of Life Research
Gepubliceerd in:

01-05-2008

Identifying response shift statistically at the individual level

Auteurs: Nancy E. Mayo, Susan C. Scott, Nandini Dendukuri, Sara Ahmed, Sharon Wood-Dauphinee

Gepubliceerd in: Quality of Life Research | Uitgave 4/2008

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Abstract

Objective

The purpose of this study was to explore whether a longitudinal comparison between reported and predicted health could be used as a method of identifying subjects who potentially experienced response shift.

Methods

A response-shift model was developed using data from a longitudinal study of stroke in which measures of stroke impact were made at study entry and at 1, 3, 6, and 12 months post stroke. Residuals from a random effects model were centered and used to create trajectories. This model was tested against a data set from a study in which the then-test had been administered. Twenty simulated data sets were also generated to examine how much of response shift could be attributed to random error.

Results

Group-based trajectory analysis identified seven trajectory groups. The majority (67%) of the 387 persons showed no response shift over time, whereas 15% lowered and 13% raised their health over time, disproportionally to that predicted.

Conclusion

Results of the validation studies were supportive that this methodology identifies response shift, but further research is required to compare results with other methodologies and other predictive models.
vorige artikel The development of the pediatric cardiac quality of life inventory: a quality of life measure for children and adolescents with heart disease
volgende artikel Individual quality of life: adaptive conjoint analysis as an alternative for direct weighting?
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Metagegevens
Titel
Identifying response shift statistically at the individual level
Auteurs
Nancy E. Mayo
Susan C. Scott
Nandini Dendukuri
Sara Ahmed
Sharon Wood-Dauphinee
Publicatiedatum
01-05-2008
Uitgeverij
Springer Netherlands
Gepubliceerd in
Quality of Life Research / Uitgave 4/2008
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-008-9329-2

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