parameters (version 0.2.0)

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,
  standardize = "refit", standardize_robust = FALSE,
  bootstrap = FALSE, iterations = 1000, component = c("all",
  "conditional", "zi", "zero_inflated"), ...)

Arguments

model

A model with zero-inflation component.

ci

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

standardize

Add standardized parameters. Can be FALSE or a character indicating the standardization method (see parameters_standardize()), such as "refit", "2sd", "smart" or "classic". The two former are based on model refitting using a standardized version of data. It is the most accurate, although computationally heavy (as it must re-fit a second model). The "smart" and "classic" are post-hoc methods, fast, but inaccurate (especially if the model includes interactions).

standardize_robust

Robust standardization. See parameters_standardize.

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.

...

Arguments passed to or from other methods (e.g., to standardize()).

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

# NOT RUN {
library(parameters)
library(pscl)

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