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Table 3 Post-sample predictive validity for 'all stroke' 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
   Missing 19 -0.03 1.00 0.278 0.357
   Total 1256 -0.04 1.00 0.464 0.337
Predicted AQoL Scale-based NIHSS = 0 580 0.20 0.75 0.494 0.134
   NIHSS = 1–5 334 0.21 0.73 0.450 0.123
   NIHSS ≥ 6 112 0.22 0.66 0.361 0.097
   Missing 19 0.25 0.73 0.403 0.141
   Total 1045 0.20 0.75 0.464 0.134
  Subscale-based NIHSS = 0 580 0.10 0.79 0.523 0.193
   NIHSS = 1–5 334 0.12 0.80 0.456 0.185
   NIHSS ≥ 6 112 0.10 0.73 0.262 0.144
   Missing 19 0.10 0.73 0.346 0.206
   Total 1045 0.10 0.80 0.460 0.202
  Item-based NIHSS = 0 581 0.05 0.80 0.513 0.191
   NIHSS = 1–5 335 -0.01 0.78 0.453 0.185
   NIHSS ≥ 6 112 0.02 0.72 0.262 0.150
   Missing 19 0.11 0.77 0.363 0.215
   Total 1047 -0.01 0.80 0.464 0.200
Mean Absolute Deviation (MAD) Scale-based NIHSS = 0 580 0.00 0.54 0.215 0.120
   NIHSS = 1–5 334 0.00 0.62 0.196 0.123
   NIHSS ≥ 6 112 0.01 0.49 0.280 0.097
   Missing 19 0.03 0.45 0.246 0.132
   Total 1045 0.00 0.62 0.216 0.121
  Subscale-based NIHSS = 0 580 0.00 0.77 0.164 0.109
   NIHSS = 1–5 334 0.00 0.62 0.161 0.117
   NIHSS ≥ 6 112 0.01 0.56 0.184 0.103
   Missing 19 0.04 0.33 0.176 0.080
   Total 1045 0.00 0.77 0.165 0.111
  Item-based NIHSS = 0 581 0.00 0.65 0.163 0.109
   NIHSS = 1–5 335 0.00 0.68 0.181 0.117
   NIHSS ≥ 6 112 0.01 0.68 0.181 0.117
   Missing 19 0.03 0.36 0.175 0.102
   Total 1047 0.00 0.68 0.163 0.111