Added optimal conditional error function design support

[morten-dreher]

No description provided.

[Copilot]

Pull Request Overview

This PR adds comprehensive support for optimal conditional error function designs to a statistical package. The optimal conditional error function approach allows for adaptive sample size re-estimation in clinical trials while maintaining strict type I error control.

Key changes include:

• Implementation of a complete design framework for optimal conditional error functions with various likelihood ratio distributions
• Addition of utility functions for calculating conditional errors, second-stage information, and overall power
• Comprehensive test suite covering different scenarios and edge cases

Reviewed Changes

Copilot reviewed 12 out of 13 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
tests/testthat/test-*.R	Six new test files providing comprehensive coverage of the optimal conditional error functionality
tests/testthat/.gitignore	Removes exclusion of R test files to include the new tests
R/parameter_descriptions.R	Adds extensive parameter documentation for the optimal conditional error design functions
R/f_design_optimal_utilities.R	Implements print, plot, and summary methods for the optimal conditional error design class
R/f_design_optimal_user.R	Provides main user-facing functions for creating designs and calculating key metrics
R/f_design_optimal_background.R	Contains internal helper functions for calculations and mathematical operations
R/class_design_optimal.R	Defines the R6 class structure for optimal conditional error trial designs

Comments suppressed due to low confidence (1)

R/f_design_optimal_background.R:353

• In the mathematical formula comment above, there's an inconsistency. The formula shows \kappa but the variable name is \eta. The code uses 'nonCentralityParameter' which corresponds to \eta, so the formula comment should use \eta consistently.

#'          \deqn{l(p_1) = \eta \cdot \sqrt{2\pi} \cdot e^{(\Phi^{-1}(1-p_1)-\eta)^2/2} \cdot \Phi(\Phi^{-1}(1-p_1)-\eta)}

[Copilot]

There is an extra closing parenthesis at the end of the comment line.

Suggested change

	#' Parameter Description: Monotonisation argument (optimal conditional error design))
	#' Parameter Description: Monotonisation argument (optimal conditional error design)

[morten-dreher]

@fpahlke Finished integration of Copilot comments, code ready for review