BGMtest {DAMisc} | R Documentation |
This function tests the five hypotheses that Berry, Golder and Milton identify as important when two quantitative variables are interacted in a linear model.
BGMtest(obj, vars, digits = 3, level = 0.05, two.sided = TRUE)
obj |
An object of class |
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 |
A matrix giving five t-tests.
Dave Armstrong
data(Duncan, package="carData")
mod <- lm(prestige ~ income*education + type, data=Duncan)
BGMtest(mod, c("income", "education"))