Table 6.

Detection power with and without randomization testing, using empirical/asymptotic p-values

method	ED dataset	TH dataset	CC dataset	AF dataset
KULL MA	3.17/3.23	4.24/4.23	2.60/2.55	3.18/3.19
KULL MA-DOW	3.26/3.04	4.23/4.09	2.26/2.26	2.83/2.80
KULL MA-WK	3.21/3.23	4.02/4.23	2.58/2.55	3.08/3.19
KULL MA-WK-DOW	3.21/3.04	4.03/4.09	2.41/2.26	2.82/2.80
EBP MA	2.48/2.50	3.28/3.29	3.42/4.16	3.90/3.99
EBP MA-DOW	2.49/2.53	3.57/3.44	3.14/4.10	4.20/4.36
EBP MA-WK	2.67/2.50	3.64/3.40	3.08/2.70	4.62/3.92
EBP MA-WK-DOW	2.92/2.59	4.02/3.75	2.90/2.47	4.53/4.00
EBG MA	2.84/2.91	4.00/4.19	4.52/4.43	4.35/4.63
EBG MA-DOW	3.05/3.01	4.92/4.66	4.67/4.50	4.83/4.79
EBG MA-WK	2.91/2.87	4.20/4.24	3.25/3.16	4.51/4.43
EBG MA-WK-DOW	2.95/3.04	4.99/4.73	3.08/2.96	4.46/4.56

Average days to detection at 1 false positive per month for "medium-sized" outbreaks injected into each dataset, using empirically determined thresholds on p-value (computed by randomization testing, using empirical/asymptotic p-values [37]) and score (without randomization testing) respectively. If there is a significant difference between the detection times with and without randomization, the better-performing method is marked in bold.