Compare baseline characteristics between two or more groups. The variables being compared can be factor and numeric variables. The function will automatically judge the type and distribution of the variables, and make statistical description and bivariate analysis.

Design and evaluate choice-based conjoint survey experiments. Generate a variety of survey designs, including random designs, frequency-based designs, and D-optimal designs, as well as "labeled" designs (also known as "alternative-specific designs"), designs with "no choice" options, and designs with dominant alternatives removed. Conveniently inspect and compare designs using a variety of metrics, including design balance, overlap, and D-error, and simulate choice data for a survey design either randomly or according to a utility model defined by user-provided prior parameters. Conduct a power analysis for a given survey design by estimating the same model on different subsets of the data to simulate different sample sizes. Bayesian D-efficient designs using the 'cea' and 'modfed' methods are obtained using the 'idefix' package by Traets et al (2020) <doi:10.18637/jss.v096.i03>. Choice simulation and model estimation in power analyses are handled using the 'logitr' package by Helveston (2023) <doi:10.18637/jss.v105.i10>.

Implementation of the d/p/q/r family of functions for a continuous analog to the standard discrete binomial with continuous size parameter and continuous support with x in [0, size + 1], following Ilienko (2013) <arXiv:1303.5990>.

Provides R users with direct access to genomic and clinical data from the 'cBioPortal' web resource via user-friendly
    functions that wrap 'cBioPortal's' existing API endpoints <https://www.cbioportal.org/api/swagger-ui/index.html>. Users can browse and query genomic data on mutations,
    copy number alterations and fusions, as well as data on tumor mutational burden ('TMB'),
    microsatellite instability status ('MSI'), 'FACETS' and select clinical data points (depending on the study). 
    See <https://www.cbioportal.org/> and Gao et al., (2013) <doi:10.1126/scisignal.2004088> for more information on the cBioPortal web resource.