Description Usage Arguments Details See Also

`pull_resid`

takes a hierarchical linear model fit as a `lmerMod`

or `lme`

object and returns various types of level-1 residuals as a
vector. Because the `pull_resid`

only calculates one type of residual,
it is more efficient than using `hlm_resid`

and indexing the
resulting tibble. `pull_resid`

is designed to be used with methods that
take a long time to run, such as the resampling methods found in the
`lmeresampler`

package.

1 2 3 4 5 6 7 8 | ```
## Default S3 method:
pull_resid(object, ...)
## S3 method for class 'lmerMod'
pull_resid(object, type = "ls", standardize = FALSE, ...)
## S3 method for class 'lme'
pull_resid(object, type = "ls", standardize = FALSE, ...)
``` |

`object` |
an object of class |

`...` |
not in use |

`type` |
which residuals should be returned. Can be either 'ls', 'eb', or 'marginal' |

`standardize` |
a logical indicating if residuals should be standardized |

`type = "ls"`

Residuals calculated by fitting separate LS regression models for each group. LS residuals are unconfounded by higher level residuals, but unreliable for small within-group sample sizes. When

`standardize = TRUE`

, residuals are standardized by sigma components of the model object.`type = "eb"`

Residuals calculated using the empirical Bayes (EB) method using maximum likelihood. EB residuals are interrelated with higher level residuals. When

`standardize = TRUE`

, residuals are standardized by sigma components of the model object.`type = "marginal"`

Marginal residuals only consider the fixed effect portion of the estimates. When

`standardize = TRUE`

, Cholesky residuals are returned.

hlm_resid

HLMdiag documentation built on May 2, 2021, 9:06 a.m.

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