Calculates marginal residuals of lmerMod and lme model objects.
# S3 method for default
resid_marginal(object, type)# S3 method for lmerMod
resid_marginal(object, type = c("raw", "pearson", "studentized", "cholesky"))
# S3 method for lme
resid_marginal(object, type = c("raw", "pearson", "studentized", "cholesky"))
an object of class lmerMod or lme.
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.
A vector of marginal residuals.
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 \(\hat{C}\hat{C}^\prime = \hat{Var}(Y)\)
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.