Calculates Efron's pseudo R2.

## Arguments

- model
Generalized linear model.

## Details

Efron's R2 is calculated by taking the sum of the squared model residuals,
divided by the total variability in the dependent variable. This R2 equals
the squared correlation between the predicted values and actual values,
however, note that model residuals from generalized linear models are not
generally comparable to those of OLS.

## References

Efron, B. (1978). Regression and ANOVA with zero-one data: Measures of
residual variation. Journal of the American Statistical Association, 73,
113-121.

## Examples

```
## Dobson (1990) Page 93: Randomized Controlled Trial:
counts <- c(18, 17, 15, 20, 10, 20, 25, 13, 12) #
outcome <- gl(3, 1, 9)
treatment <- gl(3, 3)
model <- glm(counts ~ outcome + treatment, family = poisson())
r2_efron(model)
#> [1] 0.5265152
```