Aliases: nutrition
Keywords: datasets
### ** Examples nutr.aov <- aov(gain ~ (group + age + race)^2, data = nutrition) # Summarize predictions for age group 3 nutr.emm <- emmeans(nutr.aov, ~ race * group, at = list(age="3")) emmip(nutr.emm, race ~ group)
# Hispanics seem exceptional; but this doesn't test out due to very sparse data pairs(nutr.emm, by = "group")
group = FoodStamps: contrast estimate SE df t.ratio p.value Black - Hispanic 7.50 5.97 92 1.255 0.4241 Black - White 2.08 2.84 92 0.733 0.7447 Hispanic - White -5.42 5.43 92 -0.998 0.5799 group = NoAid: contrast estimate SE df t.ratio p.value Black - Hispanic -6.17 4.36 92 -1.413 0.3383 Black - White -3.47 2.49 92 -1.394 0.3484 Hispanic - White 2.70 3.96 92 0.681 0.7750 P value adjustment: tukey method for comparing a family of 3 estimates
pairs(nutr.emm, by = "race")
race = Black: contrast estimate SE df t.ratio p.value FoodStamps - NoAid 11.17 3.45 92 3.237 0.0017 race = Hispanic: contrast estimate SE df t.ratio p.value FoodStamps - NoAid -2.50 6.55 92 -0.382 0.7034 race = White: contrast estimate SE df t.ratio p.value FoodStamps - NoAid 5.62 1.53 92 3.666 0.0004