performance (version 0.10.4)

check_zeroinflation: Check for zero-inflation in count models

Description

check_zeroinflation() checks whether count models are over- or underfitting zeros in the outcome.

Usage

check_zeroinflation(x, tolerance = 0.05)

Value

A list with information about the amount of predicted and observed zeros in the outcome, as well as the ratio between these two values.

Arguments

x

Fitted model of class merMod, glmmTMB, glm, or glm.nb (package MASS).

tolerance

The tolerance for the ratio of observed and predicted zeros to considered as over- or underfitting zeros. A ratio between 1 +/- tolerance is considered as OK, while a ratio beyond or below this threshold would indicate over- or underfitting.

Details

If the amount of observed zeros is larger than the amount of predicted zeros, the model is underfitting zeros, which indicates a zero-inflation in the data. In such cases, it is recommended to use negative binomial or zero-inflated models.

See Also

Other functions to check model assumptions and and assess model quality: check_autocorrelation(), check_collinearity(), check_convergence(), check_heteroscedasticity(), check_homogeneity(), check_model(), check_outliers(), check_overdispersion(), check_predictions(), check_singularity()

Examples

if (require("glmmTMB")) {
  data(Salamanders)
  m <- glm(count ~ spp + mined, family = poisson, data = Salamanders)
  check_zeroinflation(m)
}