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. 2024 Feb 26;152:e38. doi: 10.1017/S0950268824000311

Table 2.

Bayesian log-normal mixed-effects model of the relationship between environmental factors and geometric mean E. coli concentration at 15 beaches in the Metro Vancouver Region, 2013–2021 (other parameters, including the correlation effects of the varying slopes and the coefficients for year, are included in Table C in the Supplementary Material)

Outcome/parameter a Estimate b 95% credible interval R-hat c Bulk ESS c Tail ESS c
Fixed-level effects
Intercept 3.17 (2.79, 3.54) 1.01 439 821
Previous sample day log E. coli geometric mean 0.23 (0.13, 0.34) 1.00 901 1,496
48-h total rainfall 0.20 (0.16, 0.24) 1.00 2,998 2,692
Mean salinity −0.28 (−0.41, −0.13) 1.00 1,212 1,674
Antecedent dry days 0.01 (−0.03, 0.04) 1.00 4,860 2,965
2-h mean air temperature 0.31 (0.21, 0.41) 1.00 1,521 2,415
24-h mean UV −0.13 (−0.22, −0.05) 1.00 1,450 2,167
24-h mean air temperature * 24-h mean UV (interaction term) 0.19 (0.11, 0.26) 1.00 2,167 2,443
Group-level effects for beach (SD) 1.02 (1.00, 1.04) 1.00 6,875 2,838
a

Models conditioned on the study year as a fixed effect.

b

All the fixed-effects estimates and credible intervals are shown here on the mean-centred and standardized scale.

c

R-hat values indicate model convergence, with values closer to 1 indicating convergence. Bulk and tail effective sample size (ESS) are indicators of Markov chain sampling efficiency, with higher numbers showing more reliable results.