vcov.lmm {LMMstar} | R Documentation |
Extract The Variance-Covariance Matrix From a Linear Mixed Model
Description
Extract the variance-covariance matrix of the model coefficients of a linear mixed model.
Usage
## S3 method for class 'lmm'
vcov(
object,
effects = "mean",
robust = FALSE,
df = FALSE,
strata = NULL,
newdata = NULL,
p = NULL,
type.information = NULL,
transform.sigma = NULL,
transform.k = NULL,
transform.rho = NULL,
transform.names = TRUE,
...
)
Arguments
object |
a |
effects |
[character] Should the variance-covariance matrix for all coefficients be output ( |
robust |
[logical] Should robust standard errors (aka sandwich estimator) be output instead of the model-based standard errors. Not feasible for variance or correlation coefficients estimated by REML. |
df |
[logical] Should degree of freedom, computed using Satterthwaite approximation, for the model parameters be output. |
strata |
[character vector] When not |
newdata |
[data.frame] dataset relative to which the information should be computed. Only relevant if differs from the dataset used to fit the model. |
p |
[numeric vector] value of the model coefficients at which to evaluate the information. Only relevant if differs from the fitted values. |
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 |
transform.k |
[character] Transformation used on the variance coefficients relative to the other levels. One of |
transform.rho |
[character] Transformation used on the correlation coefficients. One of |
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. |
Details
For details about the arguments transform.sigma, transform.k, transform.rho, see the documentation of the coef.lmm function.
Value
A matrix with an attribute "df"
when argument df is set to TRUE
.