Skip to contents

Empirical Bayes predictor for random effects

Source: R/EB.R
EB.Rd

This function can estimate random effect for a given set of model estimates and new user data. The unit may be new to the model. The methods implements the EB estimate (also known as BLUP) as described in Skrondral and Rabe-Hasketh, 2009, p. 683. This function can also provide the broken stick estimate for a given level, the sum of the global (fixed) and individual (random) effects. The current implementation does not provide prediction errors.

Usage

EB(model, y, X, Z = X, BS = TRUE)

Arguments

model

An object of class brokenstick.

y

A vector of new measurements for unit j, scaled in the same metric as the fitted model.

X

A nj * p matrix with fixed effects for unit j, typically produced by bs().

Z

A nj * q matrix with random effects for unit j. The default sets Z equal to X.

BS

A logical indicating whether broken stick estimates should be returned (BS = TRUE) or the random effects (BS = FALSE). The default is TRUE.

Value

A vector of length q containing the random effect or broken stick estimates for unit j.

References

Skrondal, A., Rabe-Hesketh, S. (2009). Prediction in multilevel generalized linear models. J. R. Statist. Soc. A, 172, 3, 659-687.

Author

Stef van Buuren 2023