Get model parameters
Returns the coefficients (or posterior samples for Bayesian models) from a model. See the documentation for your object's class:
Bayesian models (rstanarm, brms, MCMCglmm, ...)
Estimated marginal means (emmeans)
Generalized additive models (mgcv, VGAM, ...)
Marginal effects models (mfx)
Mixed models (lme4, glmmTMB, GLMMadaptive, ...)
Zero-inflated and hurdle models (pscl, ...)
Models with special components (betareg, MuMIn, ...)
Hypothesis tests (htest)
get_parameters(x, ...) ## Default S3 method: get_parameters(x, verbose = TRUE, ...)
x |
A fitted model. |
... |
Currently not used. |
verbose |
Toggle messages and warnings. |
In most cases when models either return different "effects" (fixed,
random) or "components" (conditional, zero-inflated, ...), the arguments
effects and component can be used.
get_parameters() is comparable to coef(), however, the coefficients
are returned as data frame (with columns for names and point estimates of
coefficients). For Bayesian models, the posterior samples of parameters are
returned.
for non-Bayesian models, a data frame with two columns: the parameter names and the related point estimates.
for Anova (aov()) with error term, a list of parameters for the conditional and the random effects parameters
data(mtcars) m <- lm(mpg ~ wt + cyl + vs, data = mtcars) get_parameters(m)
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