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Check overdispersion of a Poisson GLM

Source: R/model_performance_overdispersion.R
check_overdispersion.Rd

Tests whether a fitted Poisson regression model is overdispersed using Pearson's chi-squared statistic.

Usage

check_overdispersion(object)

Arguments

object

A fitted model of class "glm" with family Poisson.

Value

An object of class "overdispersion", which is a list with elements:

chisq

Pearson's chi-squared statistic.

ratio

Dispersion ratio (chisq / residual df).

rdf

Residual degrees of freedom.

p

P-value from chi-squared test.

Details

  • A dispersion ratio close to 1 indicates a good Poisson fit.

  • A dispersion ratio > 1 suggests overdispersion.

  • A p-value < 0.05 indicates significant overdispersion.

  • A dispersion ratio > 2 usually means a more serious lack of fit (e.g. outliers or misspecified model).

References

Bolker B. et al. (2017). GLMM FAQ See also: performance::check_overdispersion().

Author

Martin Haringa

Examples

x <- glm(nclaims ~ area, offset = log(exposure),
         family = poisson(), data = MTPL2)
check_overdispersion(x)
#> Dispersion ratio =    1.229
#> Pearson's Chi-squared = 3684.679
#> p-value =  < 0.001
#> 
#> Overdispersion detected.