Predictions of models with nominal or continuous variables using predictInterval and lmer

prediction_ranef.R

#fit a model
library(lme4)

sleepstudy$c_Days <- as.character(sleepstudy$Days)

#same model, one continuous, one nominal
m1_c <- lmer(Reaction ~ Days + (1 | Subject), sleepstudy)
m1_n <- lmer(Reaction ~ c_Days + (1 | Subject), sleepstudy)

#Making data grid with nominal variables
library(modelr)

#make a new data set
new_c <- data_grid(data  = sleepstudy,
                   Days = seq_range(Days, 2),
                   Subject = levels(Subject)[1]) #when you have a factor, you use levels instead of unique
                  #Subject = unique(Subject)[1]) #if subject had been a character

new_n <- data_grid(data = sleepstudy,
              c_Days = unique(c_Days),
              Subject = levels(Subject)[1])

#making the predictions with a confidence interval
#https://cran.r-project.org/web/packages/merTools/vignettes/Using_predictInterval.html
library(merTools)


pred_c <- predictInterval(m1_c, newdata = new_c,
                          which = "fixed") 

pred_c <- pred_c %>%
  dplyr::bind_cols(new_c)

#nominal prediction
pred_n <- predictInterval(m1_n, newdata = new_n,
                          which = "fixed") 
pred_n <- pred_n %>%
  dplyr::bind_cols(new_n)

#plot
library(ggplot2)

ggplot() +
  geom_point(data = sleepstudy,
             aes(x = Days, y = Reaction,
                 color = Subject)) +
  geom_line(data = pred_c,
            aes(x = Days, y = fit)) +
  geom_ribbon(data = pred_c,
              aes(x = Days,
                  ymin = lwr,
                  ymax = upr),
              alpha = 0.1) +
  theme_bw()


#nominal plot
ggplot() +
  geom_point(data = sleepstudy,
             aes(x = c_Days, y = Reaction,
                 color = Subject, group = Subject)) +
  geom_line(data = pred_n,
            aes(x = c_Days, y = fit, group = Subject)) +
  geom_point(data = pred_n,
            aes(x = c_Days, y = fit, group = Subject)) +
  geom_linerange(data = pred_n,
              aes(x = c_Days,
                  ymin = lwr,
                  ymax = upr, group = Subject)) +
  theme_bw()