I have a relatively straightforward question but I haven't been able to find the answer. Consider this example:
require(emmeans) fiber.lm <- lm(strength ~ diameter*machine, data=fiber)
My hypothesis is that for each of the three machines, there is a relationship between strength and diameter, i.e. the slope for each machine is significantly different from 0. To test this, I use the
emmeans package as follows:
summary(emtrends(fiber.lm, ~"machine", var = "diameter"), infer = TRUE)
My question is: should I use multiplicity correction on the pvalues and confidence intervals (e.g. by adding
adjust="sidak") to conclude whether the slopes are significantly different from 0 or not? If yes, what may be the reason why this not done by default like when using pairwise comparisons in the
I understand there are no fixed rules about this, but I haven't been able to find discussions or examples in the literature about this specifically. In tutorials on the emmeans package, I have only found instances where no adjustment is performed (e.g. https://stats.idre.ucla.edu/r/seminars/interactions-r/#s4b and https://psu-psychology.github.io/r-bootcamp-2018/talks/correlation_regression.html#pairwise-differences-and-simple-slopes-in-regression).