Description Usage Arguments Details Value References

View source: R/residual_functions.R

Calculates marginal residuals of `lmerMod`

and `lme`

model objects.

1 2 3 4 5 6 7 8 | ```
## 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"))
``` |

`object` |
an object of class |

`type` |
a character string specifying what type of residuals should be calculated.
It is set to |

For a model of the form *Y = X β + Z b + ε*,
four types of marginal residuals can be calculated:

`raw`

*r = Y - X \hat{beta}*`pearson`

*r / √{ diag(\hat{Var}(Y)})*`studentized`

*r / √{ diag(\hat{Var}(r)})*`cholesky`

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

A vector of marginal residuals.

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.

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