Going beyond simple sample size calculations: a practitioner's guide
Brendon McConnell & Marcos Vera‐Hernández
Abstract
Basic methods to compute required sample sizes are well understood and supported by widely available software. However, researchers often oversimplify their sample size calculations, overlooking relevant features of their experimental design. This paper compiles and systematises existing methods for sample size calculations for continuous and binary outcomes, both with and without covariates, and for both clustered and non‐clustered randomised controlled trials. We present formulae accommodating panel data structures and uneven designs, and provide guidance on optimally allocating sample size between the number of clusters and the number of units per cluster. In addition, we discuss how to adjust calculations for multiple hypothesis testing and how to estimate power in more complex designs using simulation methods.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.