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# print model_parameters
Code
params
Output
# Fixed Effects
Parameter | Log-Odds | SE | 95% CI | z | p
---------------------------------------------------------------
(Intercept) | -1.36 | 0.23 | [-1.81, -0.91] | -5.98 | < .001
period [2] | -0.98 | 0.30 | [-1.57, -0.38] | -3.22 | 0.001
period [3] | -1.11 | 0.32 | [-1.75, -0.48] | -3.43 | < .001
period [4] | -1.56 | 0.42 | [-2.39, -0.73] | -3.67 | < .001
Message
Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
using a Wald z-distribution approximation.
The model has a log- or logit-link. Consider using `exponentiate =
TRUE` to interpret coefficients as ratios.
---
Code
mp
Output
# Fixed Effects
Parameter | Odds Ratio | SE | 95% CI | z | p
---------------------------------------------------------------
(Intercept) | 0.26 | 0.06 | [0.16, 0.40] | -5.98 | < .001
period [2] | 0.38 | 0.11 | [0.21, 0.68] | -3.22 | 0.001
period [3] | 0.33 | 0.11 | [0.17, 0.62] | -3.43 | < .001
period [4] | 0.21 | 0.09 | [0.09, 0.48] | -3.67 | < .001
# Random Effects
Parameter | Coefficient
----------------------------------
SD (Intercept: herd) | 0.64
Message
Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
using a Wald z-distribution approximation.
---
Code
mp
Output
# Fixed Effects
Parameter | Log-Odds | SE | 95% CI | z | p
---------------------------------------------------------------
(Intercept) | -1.40 | 0.23 | [-1.85, -0.94] | -6.02 | < .001
period [2] | -0.99 | 0.31 | [-1.59, -0.39] | -3.24 | 0.001
period [3] | -1.13 | 0.33 | [-1.77, -0.49] | -3.46 | < .001
period [4] | -1.58 | 0.43 | [-2.42, -0.74] | -3.70 | < .001
# Random Effects
Parameter | Coefficient | SE | 95% CI
--------------------------------------------------------
SD (Intercept: herd) | 0.64 | 0.18 | [0.37, 1.11]
Message
Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
using a Wald z-distribution approximation.
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