What to do if N is two?

TL;DR

This paper critiques current statistical practices in in-vivo neurophysiology, emphasizing that studies with only two animals cannot reliably infer population-level conclusions, and advocates for larger samples or alternative approaches.

Contribution

It clarifies the limitations of small-sample studies in neurophysiology and proposes that meaningful population inferences require larger sample sizes or different statistical methods.

Findings

Small-sample studies are limited to inferences about the investigated animals.

Pooling data from few animals does not support population-level conclusions.

Ethical and economic constraints often prevent larger sample sizes.

Abstract

The field of in-vivo neurophysiology currently uses statistical standards that are based on tradition rather than formal analysis. Typically, data from two (or few) animals are pooled for one statistical test, or a significant test in a first animal is replicated in one (or few) further animals. The use of more than one animal is widely believed to allow an inference on the population. Here, we explain that a useful inference on the population would require larger numbers and a different statistical approach. The field should consider to perform studies at that standard, potentially through coordinated multi-center efforts, for selected questions of exceptional importance. Yet, for many questions, this is ethically and/or economically not justifiable. We explain why in those studies with two (or few) animals, any useful inference is limited to the sample of investigated animals, irrespective of whether it is based on few animals, two animals or a single animal.