merlin_util_ev_deriv2

merlin object - should not be edited

specifies the variable which represents time

merlin_util_ev_deriv2 - returns the second derivative with respect to time of the
observation-level expected value of the outcome

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

merlin

Mixed Effects Regression for Linear, Non-Linear and User-Defined
Models

Emma Martin

Alessandro Gasparini

merlin_util_ev_deriv2 function

merlin_util_ev_deriv2 - returns the second derivative with respect to time of the
observation-level expected value of the outcome — merlin_util_ev_deriv2

merlin_util_ev_deriv2: merlin_util_ev_deriv2 - returns the second derivative with respect to time of the observation-level expected value of the outcome

Description

Usage

Arguments

References