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parameters (version 0.3.0)

model_parameters.zeroinfl: Model Parameters for Zero-Inflated Models

Description

Parameters of zero-inflated models.

Usage

# S3 method for zeroinfl
model_parameters(model, ci = 0.95,
  bootstrap = FALSE, iterations = 1000, component = c("all",
  "conditional", "zi", "zero_inflated"), standardize = NULL,
  exponentiate = FALSE, ...)

Arguments

model

A model with zero-inflation component.

ci

Confidence Interval (CI) level. Default to 0.95 (95%).

bootstrap

Should estimates be based on bootstrapped model? If TRUE, then arguments of Bayesian regressions apply (see also parameters_bootstrap()).

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, or for the zero-inflated part of the model be returned? Applies to models with zero-inflated component. component may be one of "conditional", "zi", "zero-inflated" or "all" (default). May be abbreviated.

standardize

The method used for standardizing the parameters. Can be "refit", "posthoc", "smart", "basic" or NULL (default) for no standardization. See 'Details' in standardize_parameters.

exponentiate

Logical, indicating whether or not to exponentiate the the coefficients (and related confidence intervals). This is typical for, say, logistic regressions, or more generally speaking: for models with log or logit link.

...

Arguments passed to or from other methods.

Value

A data frame of indices related to the model's parameters.

See Also

standardize_names() to rename columns into a consistent, standardized naming scheme.

Examples

Run this code
# NOT RUN {
library(parameters)
library(pscl)

data("bioChemists")
model <- zeroinfl(art ~ fem + mar + kid5 + ment | kid5 + phd, data = bioChemists)
model_parameters(model)
# }

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