View source: R/estimate_grouplevel.R
estimate_grouplevel | R Documentation |
Extract random parameters of each individual group in the context of mixed models, commonly referred to as BLUPs (Best Linear Unbiased Predictors). Can be reshaped to be of the same dimensions as the original data, which can be useful to add the random effects to the original data.
estimate_grouplevel(model, type = "random", ...)
reshape_grouplevel(x, indices = "all", group = "all", ...)
model |
A mixed model with random effects. |
type |
|
... |
Other arguments passed to or from other methods. |
x |
The output of |
indices |
A list containing the indices to extract (e.g., "Coefficient"). |
group |
A list containing the random factors to select. |
Unlike raw group means, BLUPs apply shrinkage: they are a compromise between the group estimate and the population estimate. This improves generalizability and prevents overfitting.
# lme4 model
data(mtcars)
model <- lme4::lmer(mpg ~ hp + (1 | carb), data = mtcars)
random <- estimate_grouplevel(model)
# Show group-specific effects
random
# Visualize random effects
plot(random)
# Reshape to wide data so that it matches the original dataframe...
reshaped <- reshape_grouplevel(random, indices = c("Coefficient", "SE"))
# ...and can be easily combined with the original data
alldata <- cbind(mtcars, reshaped)
# Use summary() to remove duplicated rows
summary(reshaped)
# overall coefficients
estimate_grouplevel(model, type = "total")
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