Fits relative survival regression models with or without proportional excess hazards and with the additional possibility to correct for background mortality by one or more parameter(s). These models are relevant when the observed mortality in the studied group is not comparable to that of the general population or in population-based studies where the available life tables used for net survival estimation are insufficiently stratified. In the latter case, the proposed model by Touraine et al. (2020) <doi:10.1177/0962280218823234> can be used. The user can also fit a model that relaxes the proportional expected hazards assumption considered in the Touraine et al. excess hazard model. This extension was proposed by Mba et al. (2020) <doi:10.1186/s12874-020-01139-z> to allow non-proportional effects of the additional variable on the general population mortality. In non-population-based studies, researchers can identify non-comparability source of bias in terms of expected mortality of selected individuals. An excess hazard model correcting this selection bias is presented in Goungounga et al. (2019) <doi:10.1186/s12874-019-0747-3>. This class of model with a random effect at the cluster level on excess hazard is presented in Goungounga et al. (2023) <doi:10.1002/bimj.202100210>.

Computes robust association measures that do not 
    presuppose linearity. The xi correlation (xicor) is based
    on cross correlation between ranked increments.
    The reference for the methods implemented here is 
    Chatterjee, Sourav (2020) <arXiv:1909.10140>
    This package includes the Galton peas example.

Provides a simple XML tree parser/generator. It includes
        functions to read XML files into R objects, get information out of
        and into nodes, and write R objects back to XML code. It's not as
        powerful as the 'XML' package and doesn't aim to be, but for simple
        XML handling it could be useful. It was originally developed for
        the R GUI and IDE 'RKWard' <https://rkward.kde.org>, to make plugin
        development easier.