Calculate variance-covariance matrix for GALAMM fit
Usage
# S3 method for class 'galamm'
vcov(object, parm = "beta", ...)
Arguments
- object
Object of class
galamm
returned fromgalamm
.- parm
The parameters for which the variance-covariance matrix should be calculated. Character vector with one or more of the elements "theta", "beta", "lambda", and "weights". Can also be an integer vector. When given as a character, it must be in only lowercase letters.
- ...
Further arguments passed on to other methods. Currently not used.
See also
confint.galamm()
for the method computing confidence intervals.
See vcov()
for the generic function.
Other details of model fit:
VarCorr()
,
coef.galamm()
,
confint.galamm()
,
deviance.galamm()
,
factor_loadings.galamm()
,
family.galamm()
,
fitted.galamm()
,
fixef()
,
formula.galamm()
,
llikAIC()
,
logLik.galamm()
,
nobs.galamm()
,
predict.galamm()
,
print.VarCorr.galamm()
,
ranef.galamm()
,
residuals.galamm()
,
response()
,
sigma.galamm()
Examples
# Linear mixed model with heteroscedastic residuals
mod <- galamm(
formula = y ~ x + (1 | id),
weights = ~ (1 | item),
data = hsced
)
# Extract covariance matrix for fixed regression coefficients
vcov(mod, parm = "beta")
#> [,1] [,2]
#> [1,] 0.009841573 -0.007511908
#> [2,] -0.007511908 0.014715234
# and then for weights, which gives us the variance.
vcov(mod, parm = "weights")
#> [,1]
#> [1,] 0.002459613