getVarCov.lcc: Extract Variance Components from a Fitted lcc Model

In Prof-ThiagoOliveira/lcc: Longitudinal Concordance Correlation

Extract Variance Components from a Fitted lcc Model

Description

Retrieves the variance-covariance matrix of the specified component from a fitted lcc model object. The function can extract different types of variance-covariance matrices based on the specified component type.

Usage

## S3 method for class 'lcc'
getVarCov(obj, type = "random.effects", ...)

Arguments

obj	An object of class lcc, representing a fitted longitudinal concordance correlation model.
type	Specifies the type of variance-covariance matrix to extract. Options are "random.effects" for random-effects variance-covariance, "conditional" for conditional variance-covariance of the responses, and "marginal" for marginal variance-covariance of the responses. Default is "random.effects".
...	Optional arguments passed to the underlying getVarCov function from the nlme package.

Details

This function is useful for detailed inspection of the variance components in different aspects of the model. For more information on the types of variance-covariance matrices and their interpretations, refer to the documentation of the nlme package.

See Also

lcc, summary.lcc, coef.lcc, vcov.lcc

Examples

## Not run: 
fm1 <- lcc(data = hue, subject = "Fruit", resp = "H_mean",
           method = "Method", time = "Time", qf = 2, qr = 2)
getVarCov(fm1)

## End(Not run)

Prof-ThiagoOliveira/lcc documentation built on Dec. 9, 2023, 12:10 a.m.