Get model parameters from mixed models
Returns the coefficients from a model.
## S3 method for class 'glmm'
get_parameters(x, effects = c("all", "fixed", "random"), ...)
## S3 method for class 'coxme'
get_parameters(x, effects = c("fixed", "random"), ...)
## S3 method for class 'merMod'
get_parameters(x, effects = c("fixed", "random"), ...)
## S3 method for class 'glmmTMB'
get_parameters(
x,
effects = c("fixed", "random"),
component = c("all", "conditional", "zi", "zero_inflated", "dispersion"),
...
)
## S3 method for class 'glimML'
get_parameters(x, effects = c("fixed", "random", "all"), ...)x |
A fitted model. |
effects |
Should parameters for fixed effects, random effects or both be returned? Only applies to mixed models. May be abbreviated. |
... |
Currently not used. |
component |
Which type of parameters to return, such as parameters for the
conditional model, the zero-inflated part of the model or the dispersion
term? Applies to models with zero-inflated and/or dispersion formula. Note
that the conditional component is also called count or mean
component, depending on the model. There are three convenient shortcuts:
|
In most cases when models either return different "effects" (fixed,
random) or "components" (conditional, zero-inflated, ...), the arguments
effects and component can be used.
If effects = "fixed", a data frame with two columns: the
parameter names and the related point estimates. If effects =
"random", a list of data frames with the random effects (as returned by
ranef()), unless the random effects have the same simplified
structure as fixed effects (e.g. for models from MCMCglmm).
data(mtcars) m <- lm(mpg ~ wt + cyl + vs, data = mtcars) get_parameters(m)
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