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Table 5 Post-sample predictive validity for 'severity-specific' SF-36 to AQoL algorithms

From: Can we derive an 'exchange rate' between descriptive and preference-based outcome measures for stroke? Results from the transfer to utility (TTU) technique

Data Model Group N Min Max Mean SD
Observed AQoL Validation sample NIHSS = 0 786 -0.04 1.00 0.529 0.334
   NIHSS = 1–5 337 -0.04 1.00 0.440 0.296
   NIHSS ≥ 6 114 -0.04 1.00 0.112 0.205
Predicted AQoL Subscale-based NIHSS = 0* 580 -0.05 0.93 0.523 0.266
   NIHSS = 1–5* 334 -0.02 0.92 0.450 0.252
   NIHSS ≥ 6^ 112 -1.17 0.68 0.105 0.205
  Item-based NIHSS = 0* 581 -0.08 0.90 0.532 0.264
   NIHSS = 1–5* 335 -0.16 0.93 0.447 0.261
   NIHSS ≥ 6^ 112 -0.21 0.72 0.114 0.150
Mean Absolute Deviation (MAD) Subscale-based NIHSS = 0* 580 0.00 0.76 0.137 0.115
   NIHSS = 1–5* 334 0.00 0.73 0.149 0.122
   NIHSS ≥ 6^ 112 0.00 1.14 0.125 0.179
  Item-based NIHSS = 0* 581 0.00 0.78 0.130 0.111
   NIHSS = 1–5* 335 0.00 0.76 0.141 0.114
   NIHSS ≥ 6^ 112 0.00 0.74 0.095 0.122
  1. *Predicted values obtained from 'low severity' algorithm. ^Predicted values obtained from 'moderate to severe severity' algorithm