data <- matrix(scan(),ncol=3,byrow=TRUE)
 1 1 42.5  1 1 43.3  1 1 42.9  1 2 42.2  1 2 41.4  1 2 41.8 
 2 3 48.0  2 3 44.6  2 3 43.7  2 4 42.0  2 4 42.8  2 4 42.8 
 3 5 41.7  3 5 43.4  3 5 42.5  3 6 40.6  3 6 41.8  3 6 41.8 

data
table77  <- data.frame(data)
colnames(table77)  <- c("day","run","glucose")
rm(data)

table77$day  <- as.factor(table77$day)
table77$run  <- as.factor(table77$run)


# this model assumes that day is random
# Note: SINCE run IS CODED CORRECTLY, R handles it correctly

library(afex)

table77.afex1 <- mixed(glucose ~ (1|day) + (1|run), data=table77)

summary(table77.afex1)

# this model assumes that day is fixed

table77.afex2 <- mixed(glucose ~ day + (1|run), data=table77)

summary(table77.afex2)

nice(table77.afex2)

# mean estimates and correct standard errors

library(emmeans)

emmeans(table77.afex2, ~day)