Obtaining an R squared confidence interval estimate for an lm regression

The lm_rSq_ci function uses the base R lm function to conduct a regression analysis and then computes the confidence interval for R squared.

lm_rSq_ci(
  formula,
  data = NULL,
  conf.level = 0.95,
  ci.method = c("widest", "r.con", "olkinfinn"),
  env = parent.frame()
)

Arguments

formula: The formula of the regression analysis, of the form y ~ x1 + x2, where y is the dependent variable and x1 and x2 are the predictors.
data: If the terms in the formula aren't vectors but variable names, this should be the dataframe where those variables are stored.
conf.level: The confidence of the confidence interval around the regression coefficients.
ci.method: Which method to use for the confidence interval around R squared.
env: The enviroment where to evaluate the formula.

The confidence interval

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters gjalt-jorn@a-bc.eu


### Do a simple regression analysis
lm_rSq_ci(age ~ circumference, dat=Orange);
#> [1] 0.7441914 0.9248420