SAMPLE SIZE CALCULATION FOR CROSS-SECTIONAL STUDIES

Abstract

Cross-sectional studies are commonly found in Russian medical literature. However, a significant number of these studies fail to consider sample size calculation during the planning phase, often relying on basic statistical methods. This not only restricts the usefulness of the data but also increases the risk of drawing inaccurate conclusions. The primary focus of this article is to provide a step-by-step guide for the sample size calculation process. By following our guidelines, researchers can ensure that their cross-sectional studies are adequately powered to yield meaningful and reliable results. We recognize the importance of tailoring sample size calculations to the specific objectives and data characteristics of each study, and thus our approach is flexible and adaptable. While numerous software options exist for sample size calculation, we use G*Power software for all examples in this paper. Each step in our guide is complemented by examples and detailed screenshots, ensuring that the material is both comprehensible and practically applicable. Moreover, we interpret every dialog box and screenshot to make the users comfortable with the software. The scientific quality of a study depends on detailed planning, a clear statement of the problem and the precise formulation of statistical hypotheses that are tested using the most appropriate analytical methods. Central to this process is the determination of the appropriate sample size. We hope that this article will serve as a valuable guide in the planning stage of a study, helping researchers to address a wider range of issues and reliably estimate the associations between selected exposures and the outcomes of interest with sufficient statistical power.