Provides tools for the test for the comparison of survival curves, the evaluation of the goodness-of-fit and the predictive capacity of the proportional hazards model.

Using Electronic Health Record (EHR) is difficult because most of the time the true characteristic of the patient is not available. Instead we can retrieve the International Classification of Disease code related to the disease of interest or we can count the occurrence of the Unified Medical Language System. None of them is the true phenotype which needs chart review to identify. However chart review is time consuming and costly. 'PheVis' is an algorithm which is phenotyping (i.e identify a characteristic) at the visit level in an unsupervised fashion. It can be used for chronic or acute diseases. An example of how to use 'PheVis' is available in the vignette. Basically there are two functions that are to be used: `train_phevis()` which trains the algorithm and `test_phevis()` which get the predicted probabilities. The detailed method is described in preprint by Ferté et al. (2020) <doi:10.1101/2020.06.15.20131458>.

Computes the Owen's T function or the bivariate
             normal integral using one of the following:
             modified Euler's arctangent series, tetrachoric
             series, or Vasicek's series.  For the methods,
             see Komelj, J. (2023) <doi:10.4236/ajcm.2023.134026>
             (or reprint <arXiv:2312.00011> with better typography)
             and Vasicek, O. A. (1998) <doi:10.21314/JCF.1998.015>.

Analysis of terms in linear, generalized and mixed linear models, 
	on the basis of multiple comparisons of factor contrasts.  Specially suited 
	for the analysis of interaction terms.

Analysis of features by phi delta diagrams. In particular, functions for reading data and calculating phi and delta as well as the functionality to plot it. Moreover it is possible to do further analysis on the data by generating rankings. For more information on phi delta diagrams, see also Giuliano Armano (2015) <doi:10.1016/j.ins.2015.07.028>.