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Table 2 Head-to-head performance of 6 analytical models across 500 splits (number)

From: Using verbal autopsy to measure causes of death: the comparative performance of existing methods

  CSMF accuracy Chance-corrected concordance
Tariff SSP RF PCVA King-Lu InterVA Tariff SSP RF PCVA InterVA
Adult No HCE 162 156 150 8 13 11 5 493 2 0 0
HCE 156 142 189 10 0 3 4 495 1 0 0
Child No HCE 232 166 68 15 18 1 169 195 136 0 0
HCE 264 141 69 21 5 0 236 191 55 18 0
Neonate No HCE 203 44 44 24 163 22 46 300 154 0 0
HCE 201 50 62 30 138 19 47 254 199 0 0
  1. Table 2 gives the number of 500 test-train datasets for which each method performs best for chance-corrected concordance (CCC) and cause-specific mortality fraction (CSMF) accuracy, by age and health care experience (HCE). King-Lu (KL) does not estimate individual causes so chance-corrected concordance cannot be calculated. PCVA, physician-certified VA; RF, Random Forest; SSP, Simplified Symptom Pattern; VA, verbal autopsy.