model_parameters.DirichletRegModel  R Documentation 
Parameters from multinomial or cumulative link models
## S3 method for class 'DirichletRegModel'
model_parameters(
model,
ci = 0.95,
bootstrap = FALSE,
iterations = 1000,
component = c("all", "conditional", "precision"),
standardize = NULL,
exponentiate = FALSE,
p_adjust = NULL,
keep = NULL,
drop = NULL,
verbose = TRUE,
...
)
## S3 method for class 'bifeAPEs'
model_parameters(model, ...)
## S3 method for class 'bracl'
model_parameters(
model,
ci = 0.95,
bootstrap = FALSE,
iterations = 1000,
standardize = NULL,
exponentiate = FALSE,
p_adjust = NULL,
summary = getOption("parameters_summary", FALSE),
keep = NULL,
drop = NULL,
verbose = TRUE,
...
)
## S3 method for class 'mlm'
model_parameters(
model,
ci = 0.95,
vcov = NULL,
vcov_args = NULL,
bootstrap = FALSE,
iterations = 1000,
standardize = NULL,
exponentiate = FALSE,
p_adjust = NULL,
keep = NULL,
drop = NULL,
verbose = TRUE,
...
)
## S3 method for class 'clm2'
model_parameters(
model,
ci = 0.95,
bootstrap = FALSE,
iterations = 1000,
component = c("all", "conditional", "scale"),
standardize = NULL,
exponentiate = FALSE,
p_adjust = NULL,
summary = getOption("parameters_summary", FALSE),
keep = NULL,
drop = NULL,
verbose = TRUE,
...
)
model 
A model with multinomial or categorical response value. 
ci 
Confidence Interval (CI) level. Default to 
bootstrap 
Should estimates be based on bootstrapped model? If

iterations 
The number of bootstrap replicates. This only apply in the case of bootstrapped frequentist models. 
component 
Should all parameters, parameters for the conditional model,
for the zeroinflation part of the model, or the dispersion model be returned?
Applies to models with zeroinflation and/or dispersion component. 
standardize 
The method used for standardizing the parameters. Can be

exponentiate 
Logical, indicating whether or not to exponentiate the
coefficients (and related confidence intervals). This is typical for
logistic regression, or more generally speaking, for models with log or
logit links. It is also recommended to use 
p_adjust 
Character vector, if not 
keep 
Character containing a regular expression pattern that
describes the parameters that should be included (for 
drop 
See 
verbose 
Toggle warnings and messages. 
... 
Arguments passed to or from other methods. For instance, when

summary 
Logical, if 
vcov 
Variancecovariance matrix used to compute uncertainty estimates (e.g., for robust standard errors). This argument accepts a covariance matrix, a function which returns a covariance matrix, or a string which identifies the function to be used to compute the covariance matrix.

vcov_args 
List of arguments to be passed to the function identified by
the 
Multinomial or cumulative link models, i.e. models where the
response value (dependent variable) is categorical and has more than two
levels, usually return coefficients for each response level. Hence, the
output from model_parameters()
will split the coefficient tables
by the different levels of the model's response.
A data frame of indices related to the model's parameters.
insight::standardize_names()
to rename
columns into a consistent, standardized naming scheme.
data("stemcell", package = "brglm2")
model < brglm2::bracl(
research ~ as.numeric(religion) + gender,
weights = frequency,
data = stemcell,
type = "ML"
)
model_parameters(model)
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