lmROS: Calculate Regions of Significance for 'lm()' Interactions

In MichaelJMahometa/SDSRegressionR: Helper functions for Applied Regression Analysis

Description

This function takes the work of Bauer and Curan (2005) and applies it to a linear model object produced by lm(). Currently, the function handles two types of interactions in the lm() model: (1) Quantitative by Quantitative, Johnson-Neyman Regions-of-Significance; and (2) Quantitative by Categorical, which produces a quasi Region-of-Significance marking values of the Quantitative variable at which the difference of the factor levels change significance.

Usage

lmROS(
  obj,
  interest,
  moderator,
  mod.type = 1,
  int.range = NULL,
  mod.range = NULL,
  alpha.level = 0.05
)

Arguments

obj	Model object containing either a Quantitative by Quantitative interaction or a Quantitative by Categorical interaction from lm().
interest	Variable of interest in the model. Must use quotes.
moderator	Variable designated as the moderator in the model. Must use quotes.
mod.type	Defines the TYPE of interaction. Must be an integer of 1 or 2. 1 = Quantitative by Quantitative. 2 = Quantitative by Categorical. Defaults to 1.
int.range	Optional. Defines the range of the variable of interest to be graphed. Only used when mod.type=2.
mod.range	Optional. Defines the range of the moderator to be graphed.
alpha.level	Designates the alpha for the Region-of-Significnace. Defaults to 0.5.

Details

The ROS graph produced is exported to the Global Environment as ggplot object which can be further edited.

References

Bauer, D.J. & Curran, P.J., (2005), Probing Interactions in Fixed and Multilevel Regression: Inferential and Graphical Techniques, Multivariate Behavioral Research, 40(3), 373–400.

Examples

mod <- lm(mpg ~ wt * hp, data=mtcars)
summary(mod)
lmROS(mod, "wt", "hp")

MichaelJMahometa/SDSRegressionR documentation built on March 3, 2021, 10:51 p.m.