How to only test select pairwise comparisons using emmeans? - r

Question

I have seen several examples how it might be possible to select desired pairwise comparisons, but unfortunately do not know how to apply that to my data.
Here is my abbreviated data set: https://www.dropbox.com/s/x9xjc9o0222rg0w/df.csv?dl=0
# FIXED effects: age and brain_area
df$age <- factor(df$age)
df$brain_area <- factor(df$brain_area)
# RANDOM effects: subject_ID and section
df$subject_ID <- factor(df$subject_ID)
df$section <- factor(df$section)
# dependent variable: DV
# ___________________ mixed TWO-way ANOVA
require(lme4)
require(lmerTest)
require(emmeans)
model = lmer(DV ~ age * brain_area + (1 | subject_ID), data = df)
anova(model) # significant interaction and both main effects
# ____________________ ALL pairwise comparisons
emmeans(model, pairwise~brain_area|age, adj='fdr')
# ____________________ I marked below comparisons that I would like to exclude (but keep all others)
$contrasts
age = old:
contrast estimate SE df t.ratio p.value
a - b 0.0412 0.0158 174 2.603 0.0125
a - c -0.0566 0.0158 174 -3.572 0.0007
a - control 0.3758 0.0158 174 23.736 <.0001 # exclude
a - d -0.0187 0.0158 174 -1.182 0.2387
b - c -0.0978 0.0158 174 -6.175 <.0001
b - control 0.3346 0.0158 174 21.132 <.0001 # exclude
b - d -0.0599 0.0158 174 -3.786 0.0004
c - control 0.4324 0.0158 174 27.308 <.0001
c - d 0.0378 0.0158 174 2.389 0.0199
control - d -0.3946 0.0158 174 -24.918 <.0001 # exclude
age = young:
contrast estimate SE df t.ratio p.value
a - b 0.0449 0.0147 174 3.063 0.0032
a - c -0.0455 0.0147 174 -3.105 0.0032
a - control 0.2594 0.0147 174 17.694 <.0001 # exclude
a - d 0.0202 0.0147 174 1.377 0.1702
b - c -0.0904 0.0147 174 -6.169 <.0001
b - control 0.2145 0.0147 174 14.631 <.0001 # exclude
b - d -0.0247 0.0147 174 -1.686 0.1040
c - control 0.3049 0.0147 174 20.799 <.0001
c - d 0.0657 0.0147 174 4.483 <.0001
control - d -0.2392 0.0147 174 -16.317 <.0001 # exclude
# ____________________ The line below seems to work BUT completely excludes 'control' level from factor 'brain_area'. I do not wish to completely exclude it...
emmeans(model, specs=pairwise~brain_area| age,
at = list(brain_area = c("a", "b", "c", "d")), adj='fdr' )

Answer 1

You need to provide the contrast coefficients manually. In this case, it's fairly simple to obtain all of them, then remove the ones you don't want; something like this:
EMM <- emmeans(model, ~ brain_area | age)
EMM # show the means
coef <- emmeans:::pairwise.emmc(levels(EMM)[["brain_area"]])
coef <- coef[-c(3, 6, 10)]
contrast(EMM, coef, adjust = "fdr")