1
votes

After reading the vignettes of emmeans I am still struggling with what will probably have a very simple solution.

I have simulated some data from 2 groups of 6 subjects. Measurements are being taken up to 360 minutes (ExpDelta). I have the lme model as follows:

library(lme4)
library(emmeans)

lme.model = lmer(Value ~ Treatment*ExpDelta + Baseline + (1 | SubjectNr), data = df) 

Now, I can calculate the emmeans contrasts for every time point:

emm.s <- emmeans(lme.model, pairwise ~ Treatment |  ExpDelta)  # emmeans for every time point

or only by Treatment:

emm.s <- emmeans(lme.model, 'Treatment') # emmeans over the whole investigation period
pairwise_emm<-pairs(emm.s)

Both results look as expected. But now I want to only compare the 2 Treatment groups while excluding the ExpDelta 240 and 360 group and I can't figure out how.

So my question is: what is the p-value of Placebo vs 1 mg drug Y while excluding the data of ExpDelta 240 and 360?

A reference dataset is given below:

df<-structure(list(SubjectNr = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 
5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 
7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 
10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 
12L, 12L, 12L, 12L), Treatment = structure(c(2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L), .Label = c("Placebo", "1 mg drug Y"), class = "factor"), 
    ExpDelta = c("30", "60", "90", "120", "240", "360", "30", 
    "60", "90", "120", "240", "360", "30", "60", "90", "120", 
    "240", "360", "30", "60", "90", "120", "240", "360", "30", 
    "60", "90", "120", "240", "360", "30", "60", "90", "120", 
    "240", "360", "30", "60", "90", "120", "240", "360", "30", 
    "60", "90", "120", "240", "360", "30", "60", "90", "120", 
    "240", "360", "30", "60", "90", "120", "240", "360", "30", 
    "60", "90", "120", "240", "360", "30", "60", "90", "120", 
    "240", "360"), Baseline = c(9.64, 9.64, 9.64, 9.64, 9.64, 
    9.64, 7.92, 7.92, 7.92, 7.92, 7.92, 7.92, 5.88, 5.88, 5.88, 
    5.88, 5.88, 5.88, 11.79, 11.79, 11.79, 11.79, 11.79, 11.79, 
    11.07, 11.07, 11.07, 11.07, 11.07, 11.07, 9.38, 9.38, 9.38, 
    9.38, 9.38, 9.38, 12.37, 12.37, 12.37, 12.37, 12.37, 12.37, 
    8.51, 8.51, 8.51, 8.51, 8.51, 8.51, 10.86, 10.86, 10.86, 
    10.86, 10.86, 10.86, 8.13, 8.13, 8.13, 8.13, 8.13, 8.13, 
    11.79, 11.79, 11.79, 11.79, 11.79, 11.79, 9.3, 9.3, 9.3, 
    9.3, 9.3, 9.3), Value = c(10.72, 11.58, 11.3, 11.28, 10.39, 
    10.09, 8.78, 10.71, 11.01, 9.98, 8.15, 7.85, 6.6, 8.65, 7.86, 
    7.7, 6.61, 6.88, 12.91, 13.3, 14.13, 14.57, 12.31, 11.02, 
    10.78, 12.93, 13.07, 12.07, 11.92, 11.8, 10.62, 10.62, 12.26, 
    11.7, 10.86, 8.97, 13.03, 12.86, 13.5, 11.45, 12.78, 12.7, 
    9.14, 9.08, 7.81, 8.56, 8.51, 7.73, 10.86, 11.25, 11.5, 11.21, 
    10.6, 11.59, 8.57, 7.54, 7.87, 8.07, 7.56, 8.7, 11.46, 11.33, 
    12.1, 12.18, 11.69, 11.53, 9.73, 10.01, 8.85, 9.91, 10.02, 
    9.01)), row.names = c(NA, -72L), class = "data.frame")
1
Your model was fitted to the whole dataset; so, if you truly want to exclude the data for those two treatment levels, as is stated in the question, then you need to fit s different model with those treatment levels excluded (e.g., using subset in the model fitting stage).Russ Lenth
However, if you just want to not consider certain levels, you can use the exclude‘ or include` argument when you call contrast()‘ or pairs()‘. See the documentation for pairwise.emmc for details. OR use at in the emmeans() call (see documentation for ‘ref_grid`)Russ Lenth

1 Answers

1
votes

I think the most likely interpretation of your question would be answered by

emm <- emmeans(lme.model, "Treatment", 
               at = list(ExpDelta = c("30", "60", "90", "120")))
pairs(emm)

See ? ref_grid for details on the at argument.