In the past I asked you about how to run equivalence test for interaction effects. I talked to my stats professor here at Cornell and he suggested using emmeans in R. Here is the code (though it does not create nice plots like your package):
categorical interaction equivalence test
summary(contrast(emmeans(lm1, c("x1", "x2"), weights = "equal"),
interaction = "consec"
), infer = TRUE, null=0, side="equivalence", delta=.1)
continuous interaction equivalence test
r1 <- ref_grid(lm1, at = list(x1 = c(0, 1), x2 = c(0, 1)))
summary(emmeans(r1,c("x1","x2"),contr = list(int=c(1,-1,-1,1))),infer=TRUE,null=0,delta=.1,side="equivalence")
In the past I asked you about how to run equivalence test for interaction effects. I talked to my stats professor here at Cornell and he suggested using emmeans in R. Here is the code (though it does not create nice plots like your package):
categorical interaction equivalence test
summary(contrast(emmeans(lm1, c("x1", "x2"), weights = "equal"),
interaction = "consec"
), infer = TRUE, null=0, side="equivalence", delta=.1)
continuous interaction equivalence test
r1 <- ref_grid(lm1, at = list(x1 = c(0, 1), x2 = c(0, 1)))
summary(emmeans(r1,c("x1","x2"),contr = list(int=c(1,-1,-1,1))),infer=TRUE,null=0,delta=.1,side="equivalence")