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: |
0.1.2 |
| 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: |
2021-08-16 |
| Author: |
Balint Tamasi 
[aut, cre],
Torsten Hothorn
[ctb] |
| Maintainer: |
Balint Tamasi <balint.tamasi at uzh.ch> |
| License: |
GPL-2 |
| URL: |
http://ctm.R-forge.R-project.org |
| NeedsCompilation: |
yes |
| Materials: |
NEWS |
| CRAN checks: |
tramME results |
Documentation:
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