Identifying response shift statistically at the individual level

Qual Life Res. 2008 May;17(4):627-39. doi: 10.1007/s11136-008-9329-2.

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.

Publication types

  • Comparative Study
  • Validation Study

MeSH terms

  • Adaptation, Psychological*
  • Aged
  • Female
  • Health Status Indicators
  • Humans
  • Longitudinal Studies
  • Male
  • Models, Theoretical
  • Psychological Tests
  • Psychometrics
  • Quality of Life* / psychology
  • Stroke / physiopathology
  • Stroke / psychology*
  • Time Factors