Provides the user with an interactive application which can be used to facilitate the planning of dose finding studies by applying the theory of optimal experimental design.

The DoseFinding package provides functions for the design and analysis
	     of dose-finding experiments (with focus on pharmaceutical Phase
	     II clinical trials). It provides functions for: multiple contrast
	     tests, fitting non-linear dose-response models (using Bayesian and
	     non-Bayesian estimation), calculating optimal designs and an
	     implementation of the MCPMod methodology (Pinheiro et al. (2014)
	     <doi:10.1002/sim.6052>).

Utilities for converting unstructured electronic prescribing instructions into structured medication data. Extracts drug dose, units, daily dosing frequency and intervals from English-language prescriptions. Based on Karystianis et al. (2015) <doi:10.1186/s12911-016-0255-x>.

Performs sensitivity analysis for the sharp null and attributable effects in matched studies with continuous exposures and binary outcomes as described in Zhang, Small, Heng (2024) <arXiv:2401.06909>. Two of the functions require installation of the 'Gurobi' optimizer. Please see <https://www.gurobi.com/documentation/9.0/refman/ins_the_r_package.html> for guidance.

Provides a parallel backend for the %dopar% function using
        the snow package of Tierney, Rossini, Li, and Sevcikova.

Constructs dynamic optimal shrinkage estimators for the weights of the global 
  minimum variance portfolio which are reconstructed at given reallocation 
  points as derived in Bodnar, Parolya, and Thorsén (2021) (<arXiv:2106.02131>).
  Two dynamic shrinkage estimators are available in this package. One using 
  overlapping samples while the other use nonoverlapping samples.

Estimates dose-response relations from summarized dose-response
    data and to combines them according to principles of (multivariate)
    random-effects models.

A small package containing helper utilities for creating functions
    for computing statistics.