Addressing selective reporting of experiments through predefined exclusion criteria.

Area of Science:

• Life Sciences
• Scientific Publishing

Background:

• Research articles often prioritize clear narratives, leading to the exclusion of unsuccessful experiments.
• Excluding experiments post-data analysis can introduce reporting bias into scientific literature.

Purpose of the Study:

• To discuss the balance between narrative clarity and comprehensive reporting in life sciences research.
• To propose predefining exclusion criteria as a method to mitigate reporting bias.

Main Methods:

• Discussion of current practices in scientific reporting.
• Analysis of the implications of excluding non-working experiments.

Main Results:

• The practice of excluding 'failed' experiments can lead to significant reporting bias.
• A clear story in research papers may come at the cost of complete data representation.

Conclusions:

• Researchers should consider predefining criteria for experiment exclusion before data collection.
• Adopting predefined exclusion criteria can enhance the thoroughness and reduce bias in research reporting.