p-values for Models with Zero-Inflation

This function attempts to return, or compute, p-values of hurdle and zero-inflated models.

Usage

# S3 method for zcpglm
p_value(model, component = c("all", "conditional", "zi", "zero_inflated"), ...)

# S3 method for zeroinfl
p_value(
  model,
  component = c("all", "conditional", "zi", "zero_inflated"),
  method = NULL,
  verbose = TRUE,
  ...
)

Arguments

model

A statistical model.

component

Model component for which parameters should be shown. See the documentation for your object's class in model_parameters() or p_value() for further details.

...

Additional arguments

method

Method for computing degrees of freedom for confidence intervals (CI) and the related p-values. Allowed are following options (which vary depending on the model class): "residual", "normal", "likelihood", "satterthwaite", "kenward", "wald", "profile", "boot", "uniroot", "ml1", "betwithin", "hdi", "quantile", "ci", "eti", "si", "bci", or "bcai". See section Confidence intervals and approximation of degrees of freedom in model_parameters() for further details.

verbose

Toggle warnings and messages.

Value

A data frame with at least two columns: the parameter names and the p-values. Depending on the model, may also include columns for model components etc.

Examples

if (require("pscl", quietly = TRUE)) {
  data("bioChemists")
  model <- zeroinfl(art ~ fem + mar + kid5 | kid5 + phd, data = bioChemists)
  p_value(model)
  p_value(model, component = "zi")
}
#>          Parameter          p     Component
#> 5 zero_(Intercept) 0.04463504 zero_inflated
#> 6        zero_kid5 0.41462254 zero_inflated
#> 7         zero_phd 0.02485159 zero_inflated