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Table 3 Summary of Poisson regression models used in this study

From: Assessing trends and predictors of tuberculosis in Taiwan

Poisson regression modela

RMSE

Hwalien County

  

Y ( t ) =exp β 0 + β 1 t + β 2 t 2 + β 3 ∑ n = 1 5 sin ( 2 n π t ∕ 12 ) + β 4 ∑ n = 1 5 cos ( 2 n π t ∕ 12 ) + β 5 T mean , t - 3

2.66

(T1)

Y ( t ) =exp β 0 + β 1 t + β 2 t 2 + β 3 ∑ n = 1 5 sin ( 2 n π t ∕ 12 ) + β 4 ∑ n = 1 5 cos ( 2 n π t ∕ 12 ) + β 5 T mean , t - 3 + β 6 a g e t

2.48

(T2)

Y ( t ) =exp β 0 + β 1 t + β 2 t 2 + β 3 ∑ n = 1 5 sin ( 2 n π t ∕ 12 ) + β 4 ∑ n = 1 5 cos ( 2 n π t ∕ 12 ) + β 5 T mean , t - 3 + β 6 a g e t + β 7 m a l e t + β 8 f e m a l e t

2.34

(T3)

Taitung County

  

Y ( t ) =exp β 0 + β 1 t + β 2 t 2 + β 3 ∑ n = 1 5 sin ( 2 n π t ∕ 12 ) + β 4 ∑ n = 1 5 cos ( 2 n π t ∕ 12 ) + β 5 T max , t - 2

2.64

(T4)

Y ( t ) =exp β 0 + β 1 t + β 2 t 2 + β 3 ∑ n = 1 5 sin ( 2 n π t ∕ 12 ) + β 4 ∑ n = 1 5 cos ( 2 n π t ∕ 12 ) + β 5 T max , t - 2 + β 6 a g e t

2.63

(T5)

Y ( t ) =exp β 0 + β 1 t + β 2 t 2 + β 3 ∑ n = 1 5 sin ( 2 n π t ∕ 12 ) + β 4 ∑ n = 1 5 cos ( 2 n π t ∕ 12 ) + β 5 T max , t - 2 + β 6 a g e t + β 7 m a l e t + β 8 f e m a l e t

2.63

(T6)

  1. a Y(t) represents expected incidence rate of tuberculosis, β 0 stands for intercept, β 1 stands for linear time trend, β 2 stands for quadratic time trend, β 3 and β 4 stands for the seasonality, β 5 stands for monthly maximum and mean temperature (°C), t - 3 in the subscript represents the 3-month lag time and t - 2 in the subscript represents the 2-month lag time, β 6 stands for the effect for age, β 7 stands for the effect for male, and β 8 stands for the effect for female.
  2. RMSE = Root mean squared error.
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