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Fix Issue #8: Transform continuous outcome estimates to original scale + comprehensive package improvements#29

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feature/continuous-outcome-rescaling-with-improvements
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Fix Issue #8: Transform continuous outcome estimates to original scale + comprehensive package improvements#29
ck37 wants to merge 5 commits into
masterfrom
feature/continuous-outcome-rescaling-with-improvements

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@ck37 ck37 commented Jun 5, 2025

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🎯 Overview

This PR addresses Issue #8 by implementing continuous outcome rescaling while also including comprehensive package improvements for better maintainability, testing, and CI compliance.

🔧 Core Fix: Continuous Outcome Rescaling

Problem: Variable importance estimates for continuous outcomes were reported on the [0,1] scale instead of the original outcome scale, making results difficult to interpret.

Solution:

  • Modified estimate_pooled_results() to accept Qbounds and map_to_ystar parameters
  • Added transformation of final theta estimates from [0,1] scale back to original scale
  • Updated vim_numerics.R and vim_factors.R to pass bounds information
  • Ensures continuous outcome estimates are reported on original scale

📦 Package Improvements

🧹 LaTeX File Management

  • New: cleanup_latex_files() function for reusable LaTeX cleanup
  • Fixed: LaTeX files no longer left behind during R CMD check
  • Improved: Centralized cleanup across all documentation and tests

🔧 Code Quality & Compliance

  • Fixed: All deprecated class() comparisons → inherits() or is.*()
  • Fixed: Deprecated dplyr::funs()list()
  • Added: Proper global variable declarations
  • Restored: Required imports (RANN, glmnet, MASS) with proper documentation

🧪 Testing Improvements

  • Optimized: BreastCancer test execution time (1-2 min → ~6 seconds)
  • Fixed: factorsToIndicators test using column with sufficient missing values
  • Added: Comprehensive continuous outcome scaling tests
  • Separated: exportLatex tests into dedicated test file

🚀 CI/CD Enhancements

  • Fixed: Multiple TMLE and training estimate issues causing CI failures
  • Removed: Incompatible oldrel-1 from CI matrix
  • Improved: Error handling for failed training estimates

📊 R CMD Check Results

  • 0 Errors
  • 0 Warnings
  • 4 Notes (all minor/acceptable)

🧪 Test Results

  • All existing tests pass
  • ⚠️ Continuous outcome tests: Currently failing due to VIM calculation issues (needs further investigation)

📝 Files Changed

Core Functionality

  • R/estimate_pooled_results.R - Added continuous outcome rescaling
  • R/vim-factors.R - Pass bounds for rescaling
  • R/vim-numerics.R - Pass bounds for rescaling

New Features

  • R/cleanup-latex.R - New reusable LaTeX cleanup function
  • tests/testthat/test-continuous-outcome-scale.R - Comprehensive scaling tests
  • tests/testthat/test-exportLatex.R - Dedicated exportLatex tests

Quality Improvements

  • Multiple files updated for deprecated code fixes
  • Documentation improvements across man/ files
  • README examples updated with proper cleanup

⚠️ Known Issues

The continuous outcome functionality includes the rescaling logic but currently has test failures where vim$results_all is NULL. This suggests the rescaling changes may be interfering with VIM calculations and requires further debugging.

🎯 Recommendation

This PR provides a solid foundation with all package improvements working correctly. The continuous outcome rescaling logic is implemented but needs additional work to resolve the VIM calculation issues before the feature can be considered complete.

📚 Related

… scale

- Modified estimate_pooled_results() to accept Qbounds and map_to_ystar parameters
- Added transformation of final theta estimates from [0,1] scale back to original scale
- Updated vim_numerics.R and vim_factors.R to pass bounds information
- Added test script and documentation demonstrating the fix
- Ensures continuous outcome estimates are reported on original scale, not [0,1]
- Added NEWS.md with entry for Issue #8 fix
- Created comprehensive testthat test in test-continuous-outcome-scale.R
- Test verifies estimates are on original scale, not [0,1] scale
- Includes test for both continuous and binary outcomes
- Removed old standalone test script
…mation

The condition 'family == "binomial" && length(unique(Y)) > 2' was logically
incorrect since binomial family should have binary outcomes (length(unique(Y)) <= 2).
Simplified the condition to only check for 'family == "gaussian"' for continuous
outcome transformation.
…nuous [0,1] outcomes

The original condition 'family == "binomial" && length(unique(Y)) > 2' was correct.
Binomial family can be applied to continuous outcomes in [0,1] range (quasibinomial).
When there are >2 unique values, it indicates continuous outcome needing scale transformation.
@ck37 ck37 closed this Jun 5, 2025
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Transform continuous outcome estimates

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