Calculate Overall Survival or Recurrence-Free Survival for breast cancer patients, using 'NHS Predict'.
The time interval for the estimation can be set up to 15 years, with default at 10.
Incremental therapy benefits are estimated for hormone therapy, chemotherapy, trastuzumab, and bisphosphonates.
An additional function, suited for SCAN audits, features a more user-friendly version of the code, with fewer inputs, but necessitates
the correct standardised inputs.
This work is not affiliated with the development of 'NHS Predict' and its underlying statistical model.
Details on 'NHS Predict' can be found at: <doi:10.1186/bcr2464>.
The web version of 'NHS Predict': <https://breast.predict.nhs.uk/>.
A small dataset of 50 fictional patient observations is provided for the purpose of running examples with the main two functions,
and an additional dataset is provided for running example with the dedicated SCAN function.

Tools for Working with NHS Number Checksums
c(
person("Mark", "Sellors", , "rstuff@5vcc.com", c("aut", "cre", "cph"))
)
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.

c(
person("Mark", "Sellors", , "rstats@5vcc.com", c("aut", "cre", "cph"))
)

person("Nils", "Myszkowski", email = "nmyszkowski@pace.edu", role = c("aut", "cre"))
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.