tramME: Transformation Models with Mixed Effects

Likelihood-based estimation of mixed-effects transformation models using the Template Model Builder (TMB, Kristensen et al., 2016, <doi:10.18637/jss.v070.i05>). The technical details of transformation models are given in Hothorn et al. (2018, <doi:10.1111/sjos.12291>). Likelihood contributions of exact, randomly censored (left, right, interval) and truncated observations are supported. The random effects are assumed to be normally distributed on the scale of the transformation function, the marginal likelihood is evaluated using the Laplace approximation, and the gradients are calculated with automatic differentiation (AD).

Version:	0.1.1
Depends:	R (≥ 3.6.0), tram (≥ 0.3.2), mlt (≥ 1.1.0)
Imports:	alabama, lme4 (≥ 1.1.19), Matrix, methods, nlme, TMB (≥ 1.7.15), stats, variables (≥ 1.0.2), basefun (≥ 1.0.6), mvtnorm, numDeriv, MASS, coneproj
LinkingTo:	TMB, RcppEigen
Suggests:	multcomp, parallel, survival, knitr, coxme, ordinal, ordinalCont, ggplot2
Published:	2021-04-13
Author:	Balint Tamasi [aut, cre], Torsten Hothorn [ctb]
Maintainer:	Balint Tamasi <balint.tamasi at uzh.ch>
License:	GPL-2
NeedsCompilation:	yes
Materials:	NEWS
CRAN checks:	tramME results

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