Implements the general template for collaborative targeted maximum likelihood estimation. It also provides several commonly used C-TMLE instantiation, like the vanilla/scalable variable-selection C-TMLE (Ju et al. (2017) <doi:10.1177/0962280217729845>) and the glmnet-C-TMLE algorithm (Ju et al. (2017) <arXiv:1706.10029>).

Implements a basis function or functional data analysis framework
             for several techniques of multivariate analysis in continuous-time 
             setting. Specifically, we introduced continuous-time analogues of
             several classical techniques of multivariate analysis, such as 
             principal component analysis, canonical correlation analysis, 
             Fisher linear discriminant analysis, K-means clustering, and so 
             on. Details are in Biplab Paul, Philip T. Reiss and Erjia Cui (2023) 
             "Continuous-time multivariate analysis" <doi:10.48550/arXiv.2307.09404>.

The Clinical Trials Network (CTN) of the U.S. National Institute
  of Drug Abuse sponsored the CTN-0094 research team to harmonize data sets
  from three nationally-representative clinical trials for opioid use disorder
  (OUD). The CTN-0094 team herein provides a coded collection of trial outcomes
  and endpoints used in various OUD clinical trials over the past 50 years.
  These coded outcome functions are used to contrast and cluster different
  clinical outcome functions based on daily or weekly patient urine screenings.
  Note that we abbreviate urine drug screen as "UDS" and urine opioid screen as
  "UOS". For the example data sets (based on clinical trials data harmonized by
  the CTN-0094 research team), UDS and UOS are largely interchangeable.

A system containing easy-to-use tools to compute the bioequivalence assessment in the univariate framework using the methods proposed in Boulaguiem et al. (2023) <doi:10.1101/2023.03.11.532179>.

Estimation of quantile regression models for survival data.

A system for querying, retrieving and analyzing
        protocol- and results-related information on clinical trials from
        four public registers, the 'European Union Clinical Trials Register'
        ('EUCTR', <https://www.clinicaltrialsregister.eu/>), 
        'ClinicalTrials.gov' (<https://clinicaltrials.gov/> and also 
        translating queries the retired classic interface), the 
        'ISRCTN' (<http://www.isrctn.com/>) and the
        'European Union Clinical Trials Information System'
        ('CTIS', <https://euclinicaltrials.eu/>). 
        Trial information is downloaded, converted and stored in a database 
        ('PostgreSQL', 'SQLite', 'DuckDB' or 'MongoDB'; via package 'nodbi'). 
        Protocols, statistical analysis plans, informed consent sheets and other
        documents in registers associated with trials can also be downloaded. 
        Other functions implement trial concepts canonically across registers,
        identify deduplicated records, easily find and extract variables 
        (fields) of interest even from complex nested data as used by the 
        registers, merge variables and update queries. 
        The package can be used for monitoring, meta- and trend-analysis of
        the design and conduct as well as of the results of clinical trials 
        across registers.