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Table 7 Post-sample predictive validity for NIHSS 'all stroke' & 'severity-specific' 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 = 0 819 -0.04 1.00 0.546 0.334
   NIHSS = 1–5 312 -0.03 1.00 0.443 0.294
   NIHSS ≥ 6 132 -0.04 0.98 0.112 0.210
All stroke algorithm        
Predicted AQoL Index-based NIHSS = 0 819 0.45 0.45 0.453 0.000
   NIHSS = 1–5 312 0.46 0.48 0.466 0.007
   NIHSS ≥ 6 132 0.49 0.57 0.504 0.020
  Item-based NIHSS = 0 819 0.44 0.44 0.443 0.000
   NIHSS = 1–5 312 0.22 0.47 0.435 0.042
   NIHSS ≥ 6 132 0.22 0.47 0.428 0.061
Mean Absolute Deviation (MAD) Index-based NIHSS = 0 819 0.00 0.55 0.309 0.156
   NIHSS = 1–5 312 0.00 0.54 0.258 0.147
   NIHSS ≥ 6 132 0.02 0.60 0.431 0.124
  Item-based NIHSS = 0 819 0.00 0.56 0.312 0.157
   NIHSS = 1–5 312 0.00 0.65 0.251 0.148
   NIHSS ≥ 6 132 0.04 0.65 0.114 0.359
Severity algorithms        
Predicted AQoL Index-based NIHSS = 0* 819 0.48 0.48 0.475 0.000
   NIHSS = 1–5* 312 0.45 0.57 0.539 0.033
   NIHSS ≥ 6^ 132 -0.02 0.16 0.099 0.054
  Item-based NIHSS = 0* 819 0.46 0.46 0.461 0.000
   NIHSS = 1–5* 312 0.46 0.65 0.486 0.032
   NIHSS ≥ 6^ 132 -0.08 0.20 0.096 0.046
Mean Absolute Deviation (MAD) Index-based NIHSS = 0* 819 0.00 0.52 0.304 0.155
   NIHSS = 1–5* 312 0.00 0.58 0.262 0.160
   NIHSS ≥ 6^ 132 0.00 0.82 0.120 0.157
  Item-based NIHSS = 0* 819 0.00 0.54 0.307 0.155
   NIHSS = 1–5* 312 0.00 0.55 0.259 0.146
   NIHSS ≥ 6^ 132 0.00 0.65 0.302 0.154
  1. *Predicted values obtained from 'low severity' algorithm. ^Predicted values obtained from 'moderate to severe severity' algorithm.