iid.lmm: Extract the Influence Function From a Linear Mixed Model

In LMMstar: Repeated Measurement Models for Discrete Times

Extract the Influence Function From a Linear Mixed Model

Description

Extract the influence function from a linear mixed model.

Usage

## S3 method for class 'lmm'
iid(
  x,
  effects = "mean",
  robust = TRUE,
  type.information = NULL,
  transform.sigma = NULL,
  transform.k = NULL,
  transform.rho = NULL,
  transform.names = TRUE,
  ...
)

Arguments

x	a lmm object.
effects	[character] Should the variance-covariance matrix for all coefficients be output ("all"), or only for coefficients relative to the mean ("mean" or "fixed"), or only for coefficients relative to the variance structure ("variance"), or only for coefficients relative to the correlation structure ("correlation").
robust	[logical] If FALSE the influence function is rescaled to match the model-based standard errors. The correlation however will not (necessarily) match the model-based correlation.
type.information	[character] Should the expected information be used (i.e. minus the expected second derivative) or the observed inforamtion (i.e. minus the second derivative).
transform.sigma	[character] Transformation used on the variance coefficient for the reference level. One of "none", "log", "square", "logsquare" - see details.
transform.k	[character] Transformation used on the variance coefficients relative to the other levels. One of "none", "log", "square", "logsquare", "sd", "logsd", "var", "logvar" - see details.
transform.rho	[character] Transformation used on the correlation coefficients. One of "none", "atanh", "cov" - see details.
transform.names	[logical] Should the name of the coefficients be updated to reflect the transformation that has been used?
...	Not used. For compatibility with the generic method.

LMMstar documentation built on Nov. 9, 2023, 1:06 a.m.