Marginal residuals

Calculates marginal residuals of lmerMod and lme model objects.

# Default S3 method
resid_marginal(object, type)

# S3 method for class 'lmerMod'
resid_marginal(object, type = c("raw", "pearson", "studentized", "cholesky"))

# S3 method for class 'lme'
resid_marginal(object, type = c("raw", "pearson", "studentized", "cholesky"))

Arguments

object

an object of class lmerMod or lme.

type

a character string specifying what type of residuals should be calculated. It is set to "raw" (observed - fitted) by default. Other options include "pearson", "studentized", and "cholesky". Partial matching of arguments is used, so only the first character needs to be provided.

Value

A vector of marginal residuals.

Details

For a model of the form \(Y = X \beta + Z b + \epsilon\), four types of marginal residuals can be calculated:

raw

\(r = Y - X \hat{beta}\)

pearson

\(r / \sqrt{ diag(\hat{Var}(Y)})\)

studentized

\(r / \sqrt{ diag(\hat{Var}(r)})\)

cholesky

\(\hat{C}^{-1} r\) where \(\hat{C}\hat{C}^\prime = \hat{Var}(Y)\)

References

Singer, J. M., Rocha, F. M. M., & Nobre, J. S. (2017). Graphical Tools for Detecting Departures from Linear Mixed Model Assumptions and Some Remedial Measures. International Statistical Review, 85, 290–324.

Schabenberger, O. (2004) Mixed Model Influence Diagnostics, in Proceedings of the Twenty-Ninth SAS Users Group International Conference, SAS Users Group International.