Allows the comparison of data cohorts (DC) against a Counter 
    Factual Model (CFM) and measures the difference in terms of an efficacy 
    parameter.  Allows the application of Personalised Synthetic Controls.

Segmentation of allele-specific DNA copy number data and detection of regions with abnormal copy number within each parental chromosome.  Both tumor-normal paired and tumor-only analyses are supported.

Tools for the design of prospective studies using 
    Personalised Synthetic Controls.  Can be used in either single arm or 
    randomised studies.

Bayesian analysis of item-response theory (IRT) models,
  roll call analysis; computing highest density regions; 
  maximum likelihood estimation of zero-inflated and hurdle models for count data;
  goodness-of-fit measures for GLMs;
  data sets used in writing	and teaching; seats-votes curves.

Provides a number of functions to
  simplify and automate the scoring, comparison, and evaluation of
  different ways of creating composites of data.  It is particularly
  aimed at facilitating the creation of physiological composites of
  metabolic syndrome symptom score (MetSSS) and allostatic load (AL).
  Provides a wrapper to calculate the MetSSS on new data using the
  Healthy Hearts formula.

Provide estimation for particular cases of the power series cure rate model 
             <doi:10.1080/03610918.2011.639971>. For the distribution of the concurrent causes the 
             alternative models are the Poisson, logarithmic, negative binomial and Bernoulli (which 
             are includes in the original work), the polylogarithm model 
             <doi:10.1080/00949655.2018.1451850> and the Flory-Schulz <doi:10.3390/math10244643>. 
             The estimation procedure is based on the EM algorithm discussed in 
             <doi:10.1080/03610918.2016.1202276>.
             For the distribution of the time-to-event the alternative models are slash half-normal, 
             Weibull, gamma and Birnbaum-Saunders distributions.