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

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

		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
Adult	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
Child	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
Neonate	HCE	201	50	62	30	138	19	47	254	199	0	0

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.

ISSN: 1741-7015