Related Experiment Video
Updated: Apr 5, 2026

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
Published on: September 11, 2021
Small Sample Research: Considerations Beyond Statistical Power
Kathleen E Etz1, Judith A Arroyo2
1National Institute on Drug Abuse, National Institutes of Health, 6001 Executive Blvd., Bethesda, MD, 20852, USA. ketz@nih.gov.
Abstract:
Small sample research presents a challenge to current standards of design and analytic approaches and the underlying notions of what constitutes good prevention science. Yet, small sample research is critically important as the research questions posed in small samples often represent serious health concerns in vulnerable and underrepresented populations. This commentary considers the Special Section on small sample research and also highlights additional challenges that arise in small sample research not considered in the Special Section, including generalizability, determining what constitutes knowledge, and ensuring that research designs match community desires. It also points to opportunities afforded by small sample research, such as a focus on and increased understanding of context and the emphasis it may place on alternatives to the randomized clinical trial. The commentary urges the development and adoption of innovative strategies to conduct research with small samples.
More Related Videos
Related Concept Videos
Statistical Significance
Significance Testing: Overview
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Statistical Analysis: Overview
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Assumptions of Survival Analysis

