BGMtest: Tests the five Berry, Golder and Milton (2012) Interactive...

In davidaarmstrong/damisc: Dave Armstrong's Miscellaneous Functions

Tests the five Berry, Golder and Milton (2012) Interactive Hypothesis

Description

This function tests the five hypotheses that Berry, Golder and Milton identify as important when two quantitative variables are interacted in a linear model.

Usage

BGMtest(obj, vars, digits = 3, level = 0.05, two.sided = TRUE)

Arguments

obj	An object of class lm.
vars	A vector of two variable names giving the two quantitative variables involved in the interaction. These variables must be involved in one, and only one, interaction.
digits	Number of digits to be printed in the summary.
level	Type I error rate for the tests.
two.sided	Logical indicating whether the tests should be two-sided (if TRUE, the default) or one-sided (if FALSE).

Value

A matrix giving five t-tests.

Author(s)

Dave Armstrong

Examples

data(Duncan, package="carData")
mod <- lm(prestige ~ income*education + type, data=Duncan)
BGMtest(mod, c("income", "education"))

davidaarmstrong/damisc documentation built on Oct. 1, 2023, 3:05 p.m.