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Table 2 Posterior distributions for the main parameters on original scale

From: American foulbrood in a honeybee colony: spore-symptom relationship and feedbacks between disease and colony development

Response

Parameter

Posterior distribution

P[effect > 0]

Symptoms

Intercept

0.29 ± 0.06 (0.16, 0.43)

100

Spores

2.13 ± 0.33 (1.47, 2.91)

100

Time

1.58 ± 0.15 (1.26, 1.91)

100

Brood

1.61 ± 0.19 (1.28, 2.10)

100

Spores-Brood

0.51 ± 0.40 (− 0.26, 1.45)

91.3

Brood-Time

0.03 ± 0.22 (− 0.46, 0.52)

55.6

Spores-Time

0.55 ± 0.39 (− 0.24, 1.4)

94.3

Spores = 0

0.22 ± 0.05 (0.12, 0.34)

100

Spores

Intercept

286.08 ± 65.68 (159.83, 432.0)

100

Symptoms

3.51 ± 0.68 (2.20, 5.06)

100

Time

0.63 ± 0.08 (0.46, 0.81)

100

Bees

1.08 ± 0.15 (0.78, 1.46)

100

Symptoms-Bees

2.43 ± 0.74 (0.97, 4.17)

100

Bee-time

0.45 ± 0.19 (0.04, 0.87)

99.5

Symptoms-Time

2.88 ± 0.71 (1.57, 4.49)

100

Symptoms = 0

158.26 ± 36.58 (92.63, 241.76)

100

Symptoms = 1

228.13 ± 53.04 (123.54, 349.12)

100

Bees

Intercept

17.27 ± 0.40 (16.41, 18.08)

100

Spores

1.04 ± 0.02 (0.99, 1.10)

100

Time

1.13 ± 0.01 (1.10, 1.17)

100

Brood

1.25 ± 0.01 (1.21, 1.29)

100

Brood-Spores

0.20 ± 0.03 (0.13,0.29)

100

Brood-Time

0.11 ± 0.02 (0.06, 0.15)

100

Time-Spores

0.09 ± 0.03 (0.02,0.166)

99.7

Brood

Intercept

88.11 ± 17.36 (58.69, 127.88)

100

Symptoms

1.30 ± 0.10 (1.10, 1.59)

100

Time

0.52 ± 0.03 (0.44, 0.61)

100

Bees

1.89 ± 0.15 (1.60, 2.29)

100

Bees-Symptoms

0.58 ± 0.19 (0.16, 1.02)

99.9

Bee-Time

1.37 ± 0.16 (0.97, 1.71)

100

Symptoms-Time

0.78 ± 0.12 (0.53, 1.07)

100

  1. Show are mean ± standard deviation (with 97% credibility intervals) of the main effects and the effect probability. Posteriors are weighted based on the four selected models (except for brood as response variable, see Table 1 and text). Italic rows specify the importance of one predictor in relation to another (posterior distribution of one parameter minus the other). We also show posteriors for specific values (Spores/Symptoms = 0; Symptoms = 1; see text for further explanations)