## ---- echo = FALSE, results = "hide", message = FALSE------------------------- require("emmeans") require("ggplot2") options(show.signif.stars = FALSE) knitr::opts_chunk$set(fig.width = 4.5, class.output = "ro") ## ----------------------------------------------------------------------------- nutr.lm <- lm(gain ~ (age + group + race)^2, data = nutrition) car::Anova(nutr.lm) ## ----------------------------------------------------------------------------- emmeans(nutr.lm, ~ group * race, calc = c(n = ".wgt.")) ## ----------------------------------------------------------------------------- with(nutrition, table(race, age)) ## ----------------------------------------------------------------------------- summary(emmeans(nutr.lm, pairwise ~ group | race, at = list(age = "3")), by = NULL) ## ----------------------------------------------------------------------------- framing <- mediation::framing levels(framing$educ) <- c("NA","Ref","< HS", "HS", "> HS","Coll +") framing.glm <- glm(cong_mesg ~ age + income + educ + emo + gender * factor(treat), family = binomial, data = framing) ## ----------------------------------------------------------------------------- emmip(framing.glm, treat ~ educ | gender, type = "response") ## ----------------------------------------------------------------------------- emmip(framing.glm, treat ~ educ | gender, type = "response", cov.reduce = emo ~ treat*gender + age + educ + income) ## ----eval = FALSE------------------------------------------------------------- # emo.adj <- resid(lm(emo ~ treat*gender + age + educ + income, data = framing)) ## ----eval = FALSE------------------------------------------------------------- # emmeans(..., cov.reduce = list(x1 ~ trt, x2 ~ trt + x1, x3 ~ trt + x1 + x2)) ## ----eval = FALSE------------------------------------------------------------- # emmeans(model, "A", weights = "outer") # emmeans(emmeans(model, c("A", "B"), weights = "prop"), weights = "prop") ## ----message = FALSE---------------------------------------------------------- sapply(c("equal", "prop", "outer", "cells", "flat"), function(w) predict(emmeans(nutr.lm, ~ race, weights = w))) ## ----------------------------------------------------------------------------- mtcars.lm <- lm(mpg ~ factor(cyl)*am + disp + hp + drat + log(wt) + vs + factor(gear) + factor(carb), data = mtcars) ## ----------------------------------------------------------------------------- rg.usual <- ref_grid(mtcars.lm) rg.usual nrow(rg.usual@linfct) rg.nuis = ref_grid(mtcars.lm, non.nuisance = "cyl") rg.nuis nrow(rg.nuis@linfct) ## ----------------------------------------------------------------------------- emmeans(rg.usual, ~ cyl * am) emmeans(rg.nuis, ~ cyl * am) ## ----------------------------------------------------------------------------- predict(emmeans(mtcars.lm, ~ cyl * am, non.nuis = c("cyl", "am"), wt.nuis = "prop")) predict(emmeans(mtcars.lm, ~ cyl * am, weights = "outer")) ## ----------------------------------------------------------------------------- emmeans(mtcars.lm, ~ gear | am, non.nuis = quote(all.vars(specs))) ## ---- error = TRUE------------------------------------------------------------ ref_grid(mtcars.lm, rg.limit = 200) ## ----------------------------------------------------------------------------- summary(emmeans(nutr.lm, pairwise ~ group | race, submodel = ~ age + group*race), by = NULL) ## ----------------------------------------------------------------------------- emmeans(nutr.lm, ~ group * race, submodel = "minimal") ## ----------------------------------------------------------------------------- joint_tests(nutr.lm, submodel = "type2") ## ----------------------------------------------------------------------------- cows <- data.frame ( route = factor(rep(c("injection", "oral"), c(5, 9))), drug = factor(rep(c("Bovineumab", "Charloisazepam", "Angustatin", "Herefordmycin", "Mollycoddle"), c(3,2, 4,2,3))), resp = c(34, 35, 34, 44, 43, 36, 33, 36, 32, 26, 25, 25, 24, 24) ) cows.lm <- lm(resp ~ route + drug, data = cows) ## ----message = FALSE---------------------------------------------------------- cows.rg <- ref_grid(cows.lm) cows.rg ## ----------------------------------------------------------------------------- route.emm <- emmeans(cows.rg, "route") route.emm ## ----------------------------------------------------------------------------- drug.emm <- emmeans(cows.rg, "drug") drug.emm ## ----------------------------------------------------------------------------- pairs(route.emm, reverse = TRUE) pairs(drug.emm, by = "route", reverse = TRUE) ## ---- fig.width = 5.5--------------------------------------------------------- emmip(cows.rg, ~ drug | route) ## ---- fig.width = 5.5--------------------------------------------------------- require(ggplot2) emmip(cows.rg, ~ drug) + facet_wrap(~ route, scales = "free_x") ## ---- fig.height = 2.5, fig.width = 5.5--------------------------------------- plot(drug.emm, PIs = TRUE) + facet_wrap(~ route, nrow = 2, scales = "free_y")