Code
print(out)
Output
# Fixed Effects
Parameter | Median | 95% CI | pd | Rhat | ESS
----------------------------------------------------------------------
(Intercept) | -0.25 | [-1.28, 0.75] | 68.62% | 0.999 | 3459.00
var_binom1 | -0.64 | [-2.09, 0.64] | 83.20% | 1.000 | 2820.00
groupsb | -0.22 | [-1.35, 0.87] | 64.75% | 1.000 | 3332.00
var_cont | -0.06 | [-0.14, 0.00] | 96.65% | 1.000 | 3528.00
var_binom1:groupsb | 0.53 | [-1.70, 2.69] | 69.25% | 1.000 | 2699.00
Message
Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
using a MCMC distribution approximation.
The model has a log- or logit-link. Consider using `exponentiate =
TRUE` to interpret coefficients as ratios.
Code
print(out)
Output
# Fixed Effects
Parameter | Median | 95% CI | pd | Rhat | ESS
----------------------------------------------------------------------
(Intercept) | 0.78 | [0.28, 2.11] | 68.62% | 0.999 | 3459.00
var_binom1 | 0.53 | [0.12, 1.90] | 83.20% | 1.000 | 2820.00
groupsb | 0.80 | [0.26, 2.38] | 64.75% | 1.000 | 3332.00
var_cont | 0.94 | [0.87, 1.00] | 96.65% | 1.000 | 3528.00
var_binom1:groupsb | 1.69 | [0.18, 14.80] | 69.25% | 1.000 | 2699.00
Message
Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
using a MCMC distribution approximation.
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