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The mean was lowest using the US algorithm (0.75) and highest using the French algorithm (0.94).
Finally, while the equation by Wijeysundera used the US algorithm to score the EQ-5D, Goldsmith used the UK scoring algorithm.
The dependent variable was the EQ-5D utilities computed based on the responses to the 5 items using a US algorithm [ 34].
For instance, the worst health state was scored as -0.11 using the US algorithm, which was higher than the UK valuation for severe migraine pain reported in this study (-0.20).
SF-12 summary scores were derived using the standard US algorithm.
SF-12 physical component score (PCS-12) and mental component score (MCS-12) were derived using the standard US algorithm.
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However, our analysis also suggests that the MCID varies by disease severity; with higher estimates in those reporting greater disability due to MS. Prior studies have estimated MCID values for the US-algorithm scored EQ-5D index in a variety of disease states other than MS [ 17- 20].
Furthermore, there exists a lot of excellent work (see[18 22]) presenting us algorithms designed for (l_{2,p} -minimization.
After completion of our raw data study, the BCDSP shared with us the algorithm they used for defining patient observation periods.
Mean scores ranged from 0.86 (UK) to 0.93 (US) using the Italian algorithm, 0.88 (UK) to 0.95 (US) using the French algorithm, and 0.86 (UK) to 0.93 (US, Italy) using the UK algorithm.
(3) Finally, although the mapping conception gives us an abstract, formal conception of narrow content, it does not give us an algorithm for finding the narrow content of a particular state.
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