Transformation Models
Aalen Additive Hazards Model
(Similar to) Box-Cox Models
Continuous Outcome Logistic Regression
Competing Risk Regression
Cox Proportional Hazards Model
Proportional Reverse Time Hazards Linear Regression
Normal Linear Model
Multivariate Conditional Transformation Models
Transformation Models for Clustered Data
Permutation Transformation Tests
Ordered Categorical Regression
Doubly Robust Transformation Score Test
Transformation Score Tests and Confidence Intervals
Parametric Survival Models
Methods for Stratified Linear Transformation Models
Stratified Linear Transformation Models
Formula-based user-interfaces to specific transformation models implemented in package 'mlt' (<DOI:10.32614/CRAN.package.mlt>, <DOI:10.32614/CRAN.package.mlt.docreg>). Available models include Cox models, some parametric survival models (Weibull, etc.), models for ordered categorical variables, normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression (Lohse et al., 2017, <DOI:10.12688/f1000research.12934.1>). The underlying theory is described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>. An extension to transformation models for clustered data is provided (Barbanti and Hothorn, 2022, <DOI:10.1093/biostatistics/kxac048>). Multivariate conditional transformation models (Klein et al, 2022, <DOI:10.1111/sjos.12501>) and shift-scale transformation models (Siegfried et al, 2023, <DOI:10.1080/00031305.2023.2203177>) can be fitted as well. The package contains an implementation of a doubly robust score test, described in Kook et al. (2024, <DOI:10.1080/01621459.2024.2395588>).