r2_efron: Efron's R2

In performance: Assessment of Regression Models Performance

Efron's R2

Description

Calculates Efron's pseudo R2.

Usage

r2_efron(model)

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.

Value

The R2 value.

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)

performance documentation built on Oct. 19, 2024, 1:07 a.m.