Provides basic functions that support an implementation of (discrete) choice experiments (CEs). CEs is a question-based survey method measuring people's preferences for goods/services and their characteristics. Refer to Louviere et al. (2000) <doi:10.1017/CBO9780511753831> for details on CEs, and Aizaki (2012) <doi:10.18637/jss.v050.c02> for the package.

Suite of helper functions for data wrangling and visualization.
    The only theme for these functions is that they tend towards simple, short, and narrowly-scoped.
    These functions are built for tasks that often recur but are not large enough in scope to warrant an ecosystem of interdependent functions.

Access to the datasets and many of the functions used in "Statistics Using R: An Integrative Approach". These datasets include a subset of the National Education Longitudinal Study, the Framingham Heart Study, as well as several simulated datasets used in the examples throughout the textbook. The functions included in the package reproduce some of the functionality of 'Stata' that is not directly available in 'R'.  The package also contains a tutorial on basic data frame management, including how to handle missing data.

An implementation of the surrogate approach to residuals and 
  diagnostics for ordinal and general regression models; for details, see Liu 
  and Zhang (2017) <doi:10.1080/01621459.2017.1292915>. These residuals can be 
  used to construct standard residual plots for model diagnostics (e.g., 
  residual-vs-fitted value plots, residual-vs-covariate plots, Q-Q plots, etc.). 
  The package also provides an 'autoplot' function for producing standard 
  diagnostic plots using 'ggplot2' graphics. The package currently supports 
  cumulative link models from packages 'MASS', 'ordinal', 'rms', and 'VGAM'. 
  Support for binary regression models using the standard 'glm' function is also 
  available.

A statistical learning method to simultaneously predict a range of target phenotypes using codified and natural language processing (NLP)-derived Electronic Health Record (EHR) data. See Ahuja et al (2020) JAMIA <doi:10.1093/jamia/ocaa079> for details.