Cost-Effective ESM Studies: Integrating Budget Constraints into Sample Size Decisions

• DOI: 10.31234/osf.io/b4ev5_v3
• Publication Date: 2025-03-14T17:00:37Z
• Authors: Jordan Revol; Ginette Lafit; Olivia J Kirtley; Eva Ceulemans

The Experience Sampling Method (ESM) plays a pivotal role in investigating the dynamics of psychopathological processes in daily life. A crucial question when designing ESM studies concerns the sample size needed, defined by the number of participants (𝑁) and the number of measurement occasions per participant (𝑇). Higher 𝑁 and 𝑇 increase power, but also increase researcher and participant burden, and study cost. Current approaches for sample size planning rarely account for these feasibility and financial constraints explicitly, despite significant variations in ESM studies’ design, operational expenses, participant incentives, and compliance rates. This oversight can lead to suboptimal or unrealistic sample size planning. In this article, we extend the traditional power analysis framework to integrate budget constraints into sample size decisions. In particular, we demonstrate how to formalize budget considerations into cost functions for ESM studies and how to use these to optimally select 𝑁 and 𝑇 values. Through an illustrative example, we showcase how optimal sample size decisions strongly differ across ESM designs and associated cost functions, even when focusing on the same research questions.