olsrr (version 0.1.0)

ols_step_backward: Stepwise Backward Regression

Description

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

Usage

ols_step_backward(model, ...)
# S3 method for ols_step_backward
plot(x, model = NA, ...)

Arguments

model

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

...

other inputs

x

an object of class ols_step_backward

Value

ols_step_backward returns an object of class "ols_step_backward". An object of class "ols_step_backward" is a list containing the following components:

steps

f statistic

removed

p value of score

rsquare

degrees of freedom

aic

fitted values of the regression model

sbc

name of explanatory variables of fitted regression model

sbic

response variable

adjr

predictors

rmse

predictors

mallows_cp

predictors

indvar

predictors

References

Chatterjee, Samprit and Hadi, Ali. Regression Analysis by Example. 5th ed. N.p.: John Wiley & Sons, 2012. Print.

Examples

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

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