Code
print(mp)
Output
Parameter | Log-Odds | SE | 95% CI | z | p
----------------------------------------------------------------
(Intercept) | -1.01 | 0.26 | [-1.51, -0.50] | 3.91 | < .001
var cont | -0.42 | 0.25 | [-0.90, 0.07] | 1.70 | 0.090
var binom [1] | -0.71 | 0.62 | [-1.92, 0.50] | 1.15 | 0.250
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
print(mp)
Output
Parameter | Coefficient | SE | 95% CI | z | p
---------------------------------------------------------------------------------
cond((Int)) | -0.11 | 0.22 | [ -0.55, 0.32] | 0.52 | 0.605
cond(income) | -0.01 | 3.20e-03 | [ -0.02, -0.01] | 4.07 | < .001
zi((Int)) | -23.11 | 17557.33 | [-34434.85, 34388.63] | 1.32e-03 | 0.999
Message
Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
using a Wald z-distribution approximation.
Code
print(mp)
Output
Parameter | Coefficient | SE | 95% CI | z | p
----------------------------------------------------------------------
(Intercept) | 954.50 | 123.60 | [712.26, 1196.75] | 7.72 | < .001
gear | -24.81 | 18.54 | [-61.14, 11.52] | 1.34 | 0.181
mpg | -51.21 | 11.60 | [-73.96, -28.47] | 4.41 | < .001
mpg^2 | 0.79 | 0.26 | [ 0.29, 1.30] | 3.07 | 0.002
am [1] | -30.80 | 32.30 | [-94.11, 32.52] | 0.95 | 0.340
Message
Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
using a Wald z-distribution approximation.
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