Implements marginal structural models combined with a latent class growth analysis framework for assessing the causal effect of treatment trajectories. Based on the approach described in "Marginal Structural Models with Latent Class Growth Analysis of Treatment Trajectories" Diop, A., Sirois, C., Guertin, J.R., Schnitzer, M.E., Candas, B., Cossette, B., Poirier, P., Brophy, J., Mésidor, M., Blais, C. and Hamel, D., (2023) <doi:10.1177/09622802231202384>.

A toolbox to assist with statistical analysis of animal trajectories.
    It provides simple access to algorithms for calculating and assessing a variety of 
    characteristics such as speed and acceleration, as well as multiple measures of 
    straightness or tortuosity. Some support is provided for 3-dimensional trajectories. 
    McLean & Skowron Volponi (2018) <doi:10.1111/eth.12739>.

Getting 'TikTok' data (<https://www.tiktok.com/>) through the official 
  and unofficial APIs—in other words, you can track 'TikTok'.

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>) and a tutorial explains applications in survival analysis
  (Siegfried et al., 2025, <DOI:10.48550/arXiv.2402.06428>). 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>).