Coercing an lme4::lmer model-object (of class 'lmerMod') to a model-object of class 'lmerModLmerTest' involves computing the covariance matrix of the variance parameters and the gradient (Jacobian) of cov(beta) with respect to the variance parameters.
Arguments
- model
and lmer model-object (of class 'lmerMod') – the result of a call to
lme4::lmer()- tol
tolerance for determining of eigenvalues are negative, zero or positive
Value
an object of class 'lmerModLmerTest' which sets the following
slots:
- vcov_varpar
the asymptotic covariance matrix of the variance parameters (theta, sigma).
- Jac_list
list of Jacobian matrices; gradients of vcov(beta) with respect to the variance parameters.
- vcov_beta
the asymptotic covariance matrix of the fixed-effect regression parameters (beta; vcov(beta)).
- sigma
the residual standard deviation.
See also
the class definition in lmerModLmerTest) and
lmer
Examples
m <- lme4::lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
bm <- as_lmerModLmerTest(m)
slotNames(bm)
#> [1] "vcov_varpar" "Jac_list" "vcov_beta" "sigma" "resp"
#> [6] "Gp" "call" "frame" "flist" "cnms"
#> [11] "lower" "theta" "beta" "u" "devcomp"
#> [16] "pp" "optinfo"