The R-package lme4cens builds on lme4 to fit simple random effects models with a censored response.
It re-uses the formula-module from lme4 to facilitate model specification.
The censoring information is encoded via survival's Surv-object that allows for a flexible specification of
(a combination of) left-, right- and interval-censored responses with flexible censoring levels per observation.
The random effect structure is currently limited to the most simple case, namely models with a single random intercept.
Model fitting is via maximum likelihood (ML), residual maximum likelihood (REML) is not supported.
A good choice of starting values is helpful, although there is a heuristic in place if none are given.
The fitted parameter values may depend on the choice of starting values.
As with all non-trivial optimization problems it is good practice to check convergence with different start values.
Ideally, you would also confirm that the model fit remains the roughly the same when using different optimization routines (see the control= parameter for function lmercens).
This package is currently only available via Github. To install from within R use the following command:
remotes::install_github("lenz99/lme4cens")