Provides building blocks for allowing HTML widgets to
    communicate with each other, with Shiny or without (i.e. static .html
    files). Currently supports linked brushing and filtering.

Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D, Hejblum BP, Thiebaut R & Parast L (2022). 
             "Doubly robust evaluation of high-dimensional surrogate markers", Biostatistics <doi:10.1093/biostatistics/kxac020>. You can use these methods to determine how much of the overall treatment effect is explained by a (possibly high-dimensional) set of surrogate markers.

Contains generic functions for performing 
  cross validation and for computing diagnostic errors.

Defines classes and methods to cross-validate various
  binary classification algorithms used for "class prediction"
  problems.

Implements the cross-validation methodology from Pein and Shah (2021) <arXiv:2112.03220>. Can be customised by providing different cross-validation criteria, estimators for the change-point locations and local parameters, and freely chosen folds. Pre-implemented estimators and criteria are available. It also includes our own implementation of the COPPS procedure <doi:10.1214/19-AOS1814>.

A pair of functions for renaming and encoding data frames
             using external crosswalk files. It is especially useful when
             constructing master data sets from multiple smaller data
             sets that do not name or encode variables consistently
             across files. Based on similar commands in 'Stata'.

Fits a constrained regression model for an ordinal response with ordinal predictors and possibly others, Espinosa and Hennig (2019) <DOI:10.1007/s11222-018-9842-2>. The parameter estimates associated with an ordinal predictor are constrained to be monotonic. If a monotonicity direction (isotonic or antitonic) is not specified for an ordinal predictor by the user, then one of the available methods will either establish it or drop the monotonicity assumption. Two monotonicity tests are also available to test the null hypothesis of monotonicity over a set of parameters associated with an ordinal predictor.