Rethinking the Handling of Method Failure in Comparison Studies.

Area of Science:

• Methodological Research
• Data Analysis
• Statistical Modeling

Background:

• Comparison studies are crucial for selecting appropriate methods in data analysis.
• Method failure, such as non-convergence, is a frequent challenge in these studies.
• Current guidance on handling method failure is limited, and reporting is often neglected.

Purpose of the Study:

• To provide practical guidance on handling method failure in comparative studies.
• To address the lack of standardized approaches for dealing with method failure.
• To improve the trustworthiness and interpretability of comparison study results.

Main Methods:

• Review of common practices for handling method failure in published comparison studies.
• Analysis of classical statistics and predictive modeling approaches.
• Development of recommendations based on realistic considerations and user behavior.

Main Results:

• Existing methods like data set discarding and imputation are often inappropriate for handling method failure.
• Method failure should be viewed as a complex interplay of factors, not just a manifestation.
• Recommended strategies include fallback options reflecting real-world user actions.

Conclusions:

• Inadequate handling of method failure can lead to misleading results in comparison studies.
• Adopting recommended handling and reporting strategies enhances the reliability of evidence-based method selection.
• The study provides a framework for more robust and realistic comparison studies.