sleep_mixed_effects.R

library(lme4)
library(tidyverse)
library(broom)

data(sleepstudy, package='lme4')
df <- sleepstudy %>% as_data_frame()
df$Days <- scale(df$Days)
df
getwd()
setwd("/Users/conormcdonald/Desktop/")
#write_csv(df, "sleep_study.csv")

lme4::ranef()

df
unique(df$Subject)
sleepMod = lmer(Reaction ~ Days + (Days|Subject), data=df)
as.data.frame(ranef(sleepMod))
tidy(sleepMod)
glance(sleepMod)
re <- ranef(sleepMod)
plot(density(re$Subject[[2]] + 30.14)

fixef(sleepMod) + 30.14

augment(sleepMod)
tidy(sleepMod)

tidy(sleepMod)
aug_mod <- augment(sleepMod)

aug_mod %>% 
  filter(Subject == 308) %>% 
  ggplot(aes(Days, .fitted, colour=Subject)) + 
  geom_line(alpha = 0.4) +
  geom_point(aes(Days, Reaction))

df %>% 
  ggplot(aes(Days, Reaction, colour=Subject)) + 
  geom_point()

(2.5 * (9.1989 + 10.46)) + 251.405 + 2.2586 
ranef(sleepMod)

aug_mod %>% filter(Days == 0)
X <- model.matrix(~factor(Days), df) %>% as_data_frame() 
tidy(sleepMod)
head(X)
Z = model.matrix(~factor(sleepstudy$Subject)-1)
Z %>% View()
hist(df$Reaction)
df$Reaction

glance(sleepMod)
test <- list(mtcars, mtcars)

library(purrr)
list_dfs %>% map(~map_df(., ~trimws(.)))
typeof(res[[1]])
log(df$Days)


test <- list(df1, df2)
df1 = data.frame(name = c(' mani ','san ',' fdfg '))
df2 = data.frame(name = c(' mani ','gh ',' fdfg '))