A simple statistical framework for small sample studies.

Area of Science:

• Psychology
• Neuroscience
• Life Sciences

Background:

• Traditional research infers average population effects.
• Testing for phenomenon universality is often overlooked.
• Small sample studies lack formal evidential value calculation.

Purpose of the Study:

• Introduce a formal framework for assessing universality in small samples.
• Enable robust conclusions from minimal participant data.
• Facilitate preregistration of small-sample experimental designs.

Main Methods:

• Developed a framework using binomial probability ratios.
• Compares a universality model against a sporadic effect null hypothesis.
• Employs experimental designs maximizing sensitivity and specificity.

Main Results:

• The framework allows strong conclusions with as few as 2-5 participants.
• Demonstrates the flexibility of sequential testing.
• Provides a method for defining a priori evidence thresholds.

Conclusions:

• The approach enhances the utility and credibility of small-sample research.
• Enables researchers to draw meaningful conclusions from minimal data.
• Supports preregistration for more rigorous scientific inquiry.