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Better Inference in Neuroscience: Test Less, Estimate More.

Robert J Calin-Jageman¹

¹Neuroscience Program, Dominican University, River Forest, Illinois 60305 rcalinjageman@dom.edu.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|November 9, 2022

Summary

Neuroscience should reduce reliance on null-hypothesis significance testing (NHST) and embrace estimation (effect sizes and confidence intervals). This shift enhances research rigor and improves the interpretation of findings.

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Area of Science:

Neuroscience
Research Methodology
Statistical Inference

Background:

Null-hypothesis significance testing (NHST) is prevalent in neuroscience.
Concerns exist regarding the poor planning, execution, and interpretation of NHST.
Current practices may hinder robust scientific conclusions.

Purpose of the Study:

Advocate for reduced reliance on NHST in neuroscience.
Promote the use of estimation (effect sizes and confidence intervals).
Establish criteria for appropriate NHST application.

Main Methods:

This is an editorial, presenting a perspective on current research practices.
It argues for a shift in statistical inference methods.
It emphasizes the benefits of estimation over excessive NHST.

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Main Results:

NHST is often misused, leading to invalid interpretations.
Estimation provides more suitable approaches for exploratory research.
Estimation offers crucial context for interpreting NHST results.

Conclusions:

Neuroscience should reserve NHST for confirmatory research with quantitative predictions.
An increase in the use of estimation (effect sizes, CIs) is recommended.
This methodological adjustment aims to improve research rigor and interpretability.