I am trying to probe the following significant interaction between Condition (categorical, three levels) and time (continuous) using R emmeans package:
Original formula for the model was:
m.EDA = lmer(EDA_cs ~ Time_sd * Condition+
(1+Time_sd|Subject) +
(1+Time_sd|Video),
data=data, control = lmerControl(optimizer="bobyqa", calc.derivs = FALSE, optCtrl=list(maxfun=2e5)),na.action = "na.exclude")
I know that with emtrends I can check if the effect over time is different across the different levels of condition. E.g.:
test(emtrends(m.EDA.hm, ~Condition|Time_sd, var="Time_sd", at = list(Time_sd = seq(-1.6, 1.6, by=.3))))
But I want something more specific: testing whether FS, HH and T are significantly different from each other 1. at the beginning of time (time_sd = -2), middle of time (=0) and end of time (time=2?).
I've been reading the emmeans manual but I can't figure out a way to go about this. The closest I've found is this:
test(emmeans(m.ECG.hm, pairwise ~ Condition*Time_sd, var="Time_sd", cov.reduce=range))
Which does offer a comparison of the diff. level of condition at different times, but the results don't make any sense (the differences are significant for negative time but not towards the end of time, and from the graph we can tell it's the exact opposite)
Any emmeans experts out there? thank you!