Implements the conditional inference forest approach 
  to modeling interval-censored survival data. It also provides 
  functions to tune the parameters and evaluate the model fit. See 
  Yao et al. (2019) <arXiv:1901.04599>.

Assists in generating categorical clustered outcome data, estimating the Intracluster Correlation Coefficient (ICC) for nominal or ordinal data with 2+ categories under the resampling and method of moments (MoM) methods, with confidence intervals.

Provides functions to calculate the requisite sample size for studies where ICC is 
    the primary outcome. Can also be used for calculation of power. In both cases it
    allows the user to test the impact of changing input variables by calculating the outcome
    for several different values of input variables. Based off the work of Zou.
    Zou, G. Y. (2012). Sample size formulas for estimating intraclass correlation coefficients with
    precision and assurance. Statistics in medicine, 31(29), 3972-3981.

Estimates the intraclass correlation coefficient for trajectory data using a matrix of distances between trajectories. The distances implemented are the extended Hausdorff distances (Min et al. 2007) <doi:10.1080/13658810601073315> and the discrete Fréchet distance (Magdy et al. 2015) <doi:10.1109/IntelCIS.2015.7397286>.

Provides convenient access to the German modification of the International Classification of Diagnoses, 10th revision (ICD-10-GM). It provides functionality to aid in the identification, specification and historisation of ICD-10 codes. Its intended use is the analysis of routinely collected data in the context of epidemiology, medical research and health services research. The underlying metadata are released by the German Institute for Medical Documentation and Information <https://www.dimdi.de>, and are redistributed in accordance with their license.

Provides tools for mapping International Classification of Diseases codes to comorbidity, 
    enabling the identification and analysis of various medical conditions within healthcare data.