How does one use lsmeans to estimate the difference in two pairwise contrasts? For instance--imagine a continuous dv and two factor predictors
library(lsmeans)
library(tidyverse)
dat <- data.frame(
y = runif(30),
x1 = 1:2 %>%
factor %>%
sample(30, T),
x2 = letters[1:3] %>%
factor %>%
sample(30, T)
)
lm1 <- lm(y ~ x1 * x2, data = dat)
This call gets me the estimates of the effect of x1 by x2
lsmeans(lm1, ~ x1 | x2) %>%
pairs
returns
x2 = a:
contrast estimate SE df t.ratio p.value
1 - 2 -0.150437681 0.2688707 24 -0.560 0.5810
x2 = b:
contrast estimate SE df t.ratio p.value
1 - 2 -0.048950972 0.1928172 24 -0.254 0.8018
x2 = c:
contrast estimate SE df t.ratio p.value
1 - 2 -0.006819473 0.2125610 24 -0.032 0.9747
This is fine, but I now want the difference of these contrasts, to see if these 1 - 2 differences are themselves different according to x2 levels.
Use
lsm = lsmeans(lm1, ~ x1 * x2)
contrast(lsm, interaction = “pairwise”)