Extracts the metadata and model specifications used to calculate the coefficients of determination, such as the regression type, sample size, and degrees of freedom.
Value
A list containing the following components:
type: A string indicating the regression type ("linear" or "power").has_intercept: A logical value indicating if the model includes an intercept.n: The number of observations used in the model (excluding missing values).k: The number of estimated parameters (including the intercept if present).df_res: Residual degrees of freedom (\(n - k\)).
Details
This function provides transparency into the calculation process of the various R-squared definitions. It is particularly useful for verifying whether a model was treated as a "power" regression (log-transformed) and how the degrees of freedom were determined for adjusted R-squared values.
Note
The sample size n refers to the actual number of observations
used by lm(), which may be fewer than the rows in the original
data frame if NA values were present.
Examples
df1 <- data.frame(x = 1:6, y = c(15, 37, 52, 59, 83, 92))
model <- lm(y ~ x, data = df1)
res <- r2(model)
# Check the metadata
info <- model_info(res)
info$n
#> [1] 6
info$type
#> [1] "linear"