This method calculates the Coefficient of Discrimination D for generalized linear (mixed) models for binary data. It is an alternative to other Pseudo-R-squared values like Nakelkerke's R2 or Cox-Snell R2.

cod(x)

Arguments

x

Fitted glm or glmer model.

Value

The D Coefficient of Discrimination, also known as Tjur's R-squared value.

Note

The Coefficient of Discrimination D can be read like any other (Pseudo-)R-squared value.

References

Tjur T (2009) Coefficients of determination in logistic regression models - a new proposal: The coefficient of discrimination. The American Statistician, 63(4): 366-372

See also

r2 for Nagelkerke's and Cox and Snell's pseudo r-squared coefficients.

Examples

library(sjmisc)
#> #> Attaching package: ‘sjmisc’
#> The following object is masked from ‘package:purrr’: #> #> is_empty
data(efc) # Tjur's R-squared value efc$services <- ifelse(efc$tot_sc_e > 0, 1, 0) fit <- glm(services ~ neg_c_7 + c161sex + e42dep, data = efc, family = binomial(link = "logit")) cod(fit)
#> Tjur's D: 0.023