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# print digits model_parameters.lm
Code
params
Output
Parameter | Coefficient | SE | 95% CI | t(30) | p
------------------------------------------------------------------
(Intercept) | 37.29 | 1.88 | [33.45, 41.12] | 19.86 | < .001
wt | -5.34 | 0.56 | [-6.49, -4.20] | -9.56 | < .001
Model: mpg ~ wt (32 Observations)
Sigma: 3.046 (df = 30)
RMSE : 2.949
R2: 0.753; adjusted R2: 0.745
---
Code
params
Output
Parameter | Coefficient | SE | 95% CI | t(30) | p
------------------------------------------------------------------
(Intercept) | 37.29 | 1.88 | [33.45, 41.12] | 19.86 | < .001
wt | -5.34 | 0.56 | [-6.49, -4.20] | -9.56 | < .001
# model_parameters.glm - Gamma - print
Code
mp
Output
Parameter | Prevalence Ratio | SE | 95% CI | t(7) | p
---------------------------------------------------------------------------
(Intercept) | 245.48 | 46.72 | [173.66, 351.67] | 28.92 | < .001
u [log] | 0.55 | 0.03 | [ 0.49, 0.61] | -10.88 | < .001
Message
Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
computed using a Wald t-distribution approximation.
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