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Table 5 Best performing statistical models by data type, when missing values are either deleted or linearly interpolated

From: Methods for detecting seasonal influenza epidemics using a school absenteeism surveillance system

Data Type Model Parameters FAR ADD
ES-top     
Deleted Seasonal Mixed, DOW l = 7-8, Θ = 0.30 0.411 26.71
Interpolated Seasonal GEE l = 1, Θ = 0.15 0.350 14.29
ES-3avg     
Deleted Seasonal GEE l = 15, Θ = 0.25 0.375 29.38
Interpolated Seasonal GEE l = 6, Θ = 0.20 0.433 22.75
ES-allavg     
Deleted Seasonal Mixed l = 11, Θ = 0.25 0.313 23.63
Interpolated Seasonal Mixed, DOW l = 7, Θ = 0.20 0.299 15.13
SS-top     
Deleted Seasonal Mixed l = 4, Θ = 0.10 0.461 14.67
Interpolated LR, DOW l = 4, Θ = 0.25 0.454 9.17
SS-3avg     
Deleted Seasonal GEE, DOW l = 0, Θ = 0.25 0.420 21.00
Interpolated Seasonal Mixed l = 1, Θ = 0.15 0.422 21.57
SS-allavg     
Deleted Seasonal GEE, DOW l = 0, Θ = 0.25 0.420 21.43
Interpolated Seasonal GEE, DOW l = 0, Θ = 0.25 0.420 21.43
ES.SS-allavg     
Deleted Seasonal LR l = 11, Θ = 0.30 0.375 31.75
Interpolated Seasonal LR l = 4, Θ = 0.25 0.411 21.86
  1. The metrics for the model with the lowest FAR are shown in bold. See Table 2 for aggregation abbreviations