Provides functions for working with NHS number checksums.
    The UK's National Health Service issues NHS numbers to all users of its
    services and this package implements functions for verifying that the
    numbers are valid according to the checksum scheme the NHS use.
    Numbers can be validated and checksums created.

Free United Kingdom National Health Service (NHS) and other healthcare, or population health-related data for education and training purposes. This package contains synthetic data based on real healthcare datasets, or cuts of open-licenced official data.  This package exists to support skills development in the NHS-R community: <https://nhsrcommunity.com/>.

Provides tools for drawing Statistical Process Control (SPC) charts. This package supports the NHSE/I
  programme 'Making Data Count', and allows users to draw XmR charts, use change points and apply rules with summary
  indicators for when rules are breached.

Illustrate graphically the most common Null Hypothesis Significance Testing procedures. More specifically, this package provides functions to plot Chi-Squared, F, t (one- and two-tailed) and z (one- and two-tailed) tests, by plotting the probability density under the null hypothesis as a function of the different test statistic values. Although highly flexible (color theme, fonts, etc.), only the minimal number of arguments (observed test statistic, degrees of freedom) are necessary for a clear and useful graph to be plotted, with the observed test statistic and the p value, as well as their corresponding value labels. The axes are automatically scaled to present the relevant part and the overall shape of the probability density function. This package is especially intended for education purposes, as it provides a helpful support to help explain the Null Hypothesis Significance Testing process, its use and/or shortcomings.

The implementation of Markov Model Multiple Imputation
  with the application to COVID-19 scale, NIAID OS.

Framework is devoted to mining numerical association rules through the
  utilization of nature-inspired algorithms for optimization. Drawing inspiration
  from the 'NiaARM' 'Python' and the 'NiaARM' 'Julia' packages, this repository
  introduces the capability to perform numerical association rule mining in
  the R programming language.
  Fister Jr., Iglesias, Galvez, Del Ser, Osaba and Fister (2018) <doi:10.1007/978-3-030-03493-1_9>.