What type of study is this?

This is a Quantitative Study study.

September 19, 2025Open Access

Sample size matters: A step-by-step guide for radiologists

Key Points

Increasing sample size enhances precision and statistical power in radiological studies, leading to more reliable results.
Key factors such as variability and expected differences influence the necessary sample size calculations in research.
The paper provides examples of sample size calculations for both descriptive and comparative studies in radiology.
Using R-based software for sample size calculation simplifies the process and makes it more accessible for radiologists.

Abstract

Sample size is an essential step in any research study because it directly affects precision and statistical power. This article describes the main factors that determine the number of observations needed (power of a hypothesis test, significance criterion, minimum expected difference, variability, and asymmetry of the hypothesis test) and techniques for minimizing these factors. Our paper clearly presents examples of sample size calculations in radiology related to descriptive (mean and proportion) and comparative (two means, two proportions, intraclass correlations, and analysis of variance) studies. These examples are solved both manually and computationally using free R-based software.

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Cite This Study

Gheno et al. (Thu,) studied this question.

synapsesocial.com/papers/68d466b531b076d99fa656ea https://doi.org/https://doi.org/10.25259/jcis_36_2025

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