This method performs a Hosmer-Lemeshow goodness-of-fit-test for generalized linear (mixed) models for binary data.

hoslem_gof(x, g = 10)

Arguments

x

Fitted glm or glmer model.

g

Number of bins to divide the data. Default is 10.

Value

An object of class hoslem_test with following values:

  • chisq the Hosmer-Lemeshow chi-squared statistic

  • df degrees of freedom

  • p.value the p-value for the goodness-of-fit test

Note

A well-fitting model shows no significant difference between the model and the observed data, i.e. the reported p-value should be greater than 0.05.

References

Hosmer, D. W., & Lemeshow, S. (2000). Applied Logistic Regression. Hoboken, NJ, USA: John Wiley & Sons, Inc. doi: 10.1002/0471722146

See also

Examples

data(efc) # goodness-of-fit test for logistic regression efc$services <- ifelse(efc$tot_sc_e > 0, 1, 0) fit <- glm(services ~ neg_c_7 + c161sex + e42dep, data = efc, family = binomial(link = "logit")) hoslem_gof(fit)
#> $chisq #> [1] 6.811464 #> #> $df #> [1] 8 #> #> $p.value #> [1] 0.5571044 #> #> attr(,"class") #> [1] "hoslem_test" "list"