vcov.mlrcs

vcov.summary.mlrcs

<p>An object of class <code>mlrcs</code> or <code>summary.mlrcs</code>.</p>

object

<p>Returns the variance-covariance matrix of all estimated parameters of a fitted <code>mlrcs</code> model.</p>

Fits linear, non-linear, and user-defined mixed effects regression models following
the framework developed by Crowther (2017) <arXiv:1710.02223>. 'merlin' can fit multivariate
outcome models of any type, each of which could be repeatedly measured (longitudinal), with
any number of levels, and with any number of random effects at each level. Standard
distributions/models available include the Bernoulli, Gaussian, Poisson, beta,
negative-binomial, and time-to-event/survival models include the exponential,
Gompertz, Royston-Parmar, Weibull and general hazard model. 'merlin' provides a
flexible predictor syntax, allowing the user to define variables, random effects,
spline and fractional polynomial functions, functions of
other outcome models, and any interaction between each of them. Non-linear and
time-dependent effects are seamlessly incorporated into the predictor. 'merlin'
allows multivariate normal random effects, which are integrated out using Gaussian
quadrature or Monte-Carlo integration. Note, 'merlin' is based on the 'Stata' package
of the same name, described in Crowther (2018) <arXiv:1806.01615>.

Michael Crowther

vcov.mlrcs: Calculate Variance-Covariance Matrix for a `mlrcs` Model Object

Description

Usage

Arguments