# Load lme4 library.
library(lme4)

# Fit Model 3.1 (see chapter3_R_final.R for code to load the data).
model3.1.fit.lmer <- lmer(weight ~ treatment + sex1 + litsize +
                                treatment:sex1 + (1 | litter),
                              ratpup, REML = T)

# View results and 95% confidence intervals.
summary(model3.1.fit.lmer)
confint(model3.1.fit.lmer)

# Display the random effects (EBLUPs) from the model.
ranef(model3.1.fit.lmer)

# Plot the predicted random effects along with measures of uncertainty.
library(merTools)
REsim(model3.1.fit.lmer)
plotREsim(REsim(model3.1.fit.lmer))

# Code for obtaining p-values (if desired).
library(lmerTest)

# Model 3.1.
model3.1.fit.lmer <- lmer(weight ~ treatment + sex1 + litsize +
                                treatment:sex1 + (1 | litter),
                              ratpup, REML = T)

summary(model3.1.fit.lmer)
anova(model3.1.fit.lmer)

# Significant test for the variance component.
rand(model3.1.fit.lmer)