Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data

Table 2 Analysis based on finite mixture model. Results from the analysis of 28 antibodies based on finite mixture models, where AIC and GOF denote the Akaike’s information criterion and the Pearson’s goodness-of-fit test, respectively

Antibody	Best Mixture Model	# Components	AIC	P-value (GOF)
eba140	Skew Normal	2	23,92	0,32
eba175	Skew Normal	2	33,29	0,03
eba181	Skew Normal	2	42,9	0,03
gama	Skew-t	1	-272,19	0,24
h101	Skew-t	1	-230,91	0,33
h103	Skew Normal	1	-41,91	0,72
msp1	Skew Normal	2	25,35	0,26
msp10	Normal	2	71,52	0,07
msp2	Skew Normal	2	-24,09	0,43
msp3	Skew Normal	1	1,46	0,32
msp4	Skew Normal	2	76,23	0,04
msp5	Normal	2	-71,25	0,33
msp6	Normal	2	-168,02	0,35
msp7	Skew Normal	2	46,11	0,16
msp9	Skew Normal	2	-10,75	0,53
msrp1	Skew-t	2	-89,1	0,06
msrp2	Skew-t	1	-122,32	0,12
msrp3	Skew-t	1	-283,83	0,02
mtrap	Skew Normal	2	-213,58	0,13
pf10_0323	Skew-t	1	-344,51	0,62
pf113	Normal	2	-139,5	0,73
pf12	Skew Normal	2	-33,29	0,24
pf38	Skew Normal	2	99,41	0,05
pf41	Skew Normal	2	35,96	0,10
pff0335c	Skew Normal	2	4,83	0,04
rama	Skew Normal	2	-153,54	0,32
rhoph3	Skew Normal	2	-152,73	0,02
tlp	Skew Normal	2	-426,93	0,02

ISSN: 1756-0381