Table 5 Summary of the regression coefficients, their standard errors (SE)(x10-4) and relative bias of 48,000 simulated datasets on the impact of mixture error model on 2-pollutant Poisson regression. Results presented for the core scenario (Area: Europe, Error type: Additive-Mixture) and sensitivity analyses (N = 48,000 in each row)
Sensitivity Analysis | CRFsa: | PM2.5: β1 = 5.4a | NO2: β2 = 6a | ||||
|---|---|---|---|---|---|---|---|
Scenario | \( {\hat{\boldsymbol{\beta}}}_{\mathbf{1}} \) | (SEW)/(SEB)b | Bias (%)c | \( {\hat{\boldsymbol{\beta}}}_{\mathbf{2}} \) | (SEW)/(SEB)b | Bias (%)c | |
Main Analysis (Europe-Mixture) | 5.33 | (1.49)/(3.57) | −1.3 | 4.36 | (2.00)/(5.10) | −27.4 | |
Different “true” CRFs | Low effect CRFd | 2.66 | (1.50)/(3.53) | −1.5 | 2.19 | (2.00)/(4.79) | −27.0 |
High effect CRFe | 10.66 | (1.47)/(3.73) | −1.3 | 8.78 | (1.97)/(6.05) | −26.9 | |
Only PM2.5 effect | 4.85 | (1.50)/(3.57) | −10.2 | 0.13 | (2.02)/(4.76) | – | |
Only NO2 effect | 0.44 | (1.50)/(3.55) | – | 4.35 | (2.02)/(5.05) | −27.5 | |
Mixture error percentages | (Classical,Berkson) PM2.5: (55,45%), NO2: (45,55%) | 5.20 | (1.46)/(3.54) | −3.6 | 4.47 | (1.83)/(4.59) | −25.6 |
(Classical,Berkson) PM2.5: (70,30%), NO2: (60,40%) | 5.08 | (1.42)/(3.45) | −6.0 | 4.48 | (1.70)/(4.26) | −25.4 | |
Error type | Multiplicative | 0.83 | (0.27)/(1.92) | −84.5 | 0.61 | (0.27)/(1.68) | −90.0 |