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.
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.
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