I have been trying to compare a set of interaction contrasts using emmeans() and contrast(). However, I am having trouble applying a custom contrast and then compare it between groups. Here I added an example dataset so you can replicate what I am working with.
In summary, this dataset contains 3 factors: group, location, scenario. Location and scenario are within subject variables and group is a between subject variable. I would like to know if there is a higher measurement in location A compared to B, C and D (I set a contrast in the form c(1, -1/2, -1/2)) and then compare this contrast between groups (a contrast of contrast). So far I managed to get the contrast for each group (working with a single scenario at the moment):
library(afex)
library(emmeans)
data <- data.frame(
id = rep(c(100:189), each = 9),
group = rep(c("W", "X", "Y"), each = 90 * 3),
location = rep(c("A", "B", "C"), each = 3, times = 90),
scenario = rep(c("alpha", "beta", "gamma"), times = 270),
measurement = c(rnorm(length(id)))
)
test_aov <- aov_car(measurement ~ group * scenario * location +
Error(id/scenario * location),
data = data)
location_a_vs_all <- c(1, -1/2, -1/2)
test_effects <- emmeans(test_aov,
specs = ~ location | scenario | group,
at = list(scenario = c("alpha")))
test_contrast <- contrast(test_effects,
method = list("Location A vs All" = location_a_vs_all),
adjust = "none")
But if I try to set the argument interaction to True in the contrast() function I get an error:
test_contrast <- contrast(test_effects,
method = list("Location A vs All" = location_a_vs_all),
interaction = T,
adjust = "none")
Error in contrast.emmGrid(object, interaction[[i]], by = vars[-pos], name = nm, : 'method' must be a list, function, or the basename of an '.emmc' function
The same happens if I put my custom contrast directly in the interaction argument.
test_contrast <- contrast(test_effects,
interaction = list("Location A vs All" = location_a_vs_all),
adjust = "none")
I looked at the documentation on Interaction analysis in CRAN but I am lost on how to correctly implement what I would like to do, so I would appreciate any pointers from you. Thanks in advance!
The solution is to split the analysis in three steps:
library(afex)
library(emmeans)
data <- data.frame(
id = rep(c(100:189), each = 9),
group = rep(c("W", "X", "Y"), each = 90 * 3),
location = rep(c("A", "B", "C"), each = 3, times = 90),
scenario = rep(c("alpha", "beta", "gamma"), times = 270),
measurement = c(rnorm(length(id)))
)
test_aov <- aov_car(measurement ~ group * scenario * location +
Error(id/scenario * location),
data = data)
First I got the effects for the specific scenario:
test_effects <- emmeans(test_aov,
specs = ~ location | group,
at = list(scenario = c("alpha")))
Then I make the contrast comparing one of the locations to the other 2 (which I referred as my custom contrast in the question setup), using the "treatment vs control" method:
location_con <- contrast(test_effects,
method = "trt.vs.ctrl",
name = "A vs Others",
by = "group",
ref = 2:3)
Finally I apply a contrast of contrast to this, to compare the previous result between group W and the others, defining W as my reference level:
group_con <- contrast(location_con,
method = "trt.vs.ctrl",
by = "A vs Others",
ref = "W")