olsrr (version 0.6.0)

ols_step_backward_r2: Stepwise R-Squared backward regression

Description

Build regression model from a set of candidate predictor variables by removing predictors based on r-squared, in a stepwise manner until there is no variable left to remove any more.

Usage

ols_step_backward_r2(model, ...)
# S3 method for default
ols_step_backward_r2(
  model,
  include = NULL,
  exclude = NULL,
  progress = FALSE,
  details = FALSE,
  ...
)
# S3 method for ols_step_backward_r2
plot(x, print_plot = TRUE, details = TRUE, digits = 3, ...)

Value

List containing the following components:

model

final model; an object of class lm

metrics

selection metrics

others

list; info used for plotting and printing

Arguments

model

An object of class lm; the model should include all candidate predictor variables.

...

Other arguments.

include

Character or numeric vector; variables to be included in selection process.

exclude

Character or numeric vector; variables to be excluded from selection process.

progress

Logical; if TRUE, will display variable selection progress.

details

Logical; if TRUE, will print the regression result at each step.

x

An object of class ols_step_backward_*.

print_plot

logical; if TRUE, prints the plot else returns a plot object.

digits

Number of decimal places to display.

References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

See Also

Other backward selection procedures: ols_step_backward_adj_r2(), ols_step_backward_aic(), ols_step_backward_p(), ols_step_backward_sbc(), ols_step_backward_sbic()

Examples

# stepwise backward regression
model <- lm(y ~ ., data = surgical)
ols_step_backward_r2(model)

# final model and selection metrics
k <- ols_step_backward_aic(model)
k$metrics
k$model

# include or exclude variable
# force variables to be included in the selection process
ols_step_backward_r2(model, include = c("alc_mod", "gender"))

# use index of variable instead of name
ols_step_backward_r2(model, include = c(7, 6))

# force variable to be excluded from selection process
ols_step_backward_r2(model, exclude = c("alc_heavy", "bcs"))

# use index of variable instead of name
ols_step_backward_r2(model, exclude = c(8, 1))