Sample size justifications in Gait & Posture

Gait Posture. 2022 Feb:92:333-337. doi: 10.1016/j.gaitpost.2021.12.010. Epub 2021 Dec 11.

Abstract

Background: Context regarding how researchers determine the sample size of their experiments is important for interpreting the results and determining their value and meaning. Between 2018 and 2019, the journal Gait & Posture introduced a requirement for sample size justification in their author guidelines.

Research question: How frequently and in what ways are sample sizes justified in Gait & Posture research articles and was the inclusion of a guideline requiring sample size justification associated with a change in practice?

Methods: The guideline was not in place prior to May 2018 and was in place from 25th July 2019. All articles in the three most recent volumes of the journal (84-86) and the three most recent, pre-guideline volumes (60-62) at time of preregistration were included in this analysis. This provided an initial sample of 324 articles (176 pre-guideline and 148 post-guideline). Articles were screened by two authors to extract author data, article metadata and sample size justification data. Specifically, screeners identified if (yes or no) and how sample sizes were justified. Six potential justification types (Measure Entire Population, Resource Constraints, Accuracy, A priori Power Analysis, Heuristics, No Justification) and an additional option of Other/Unsure/Unclear were used.

Results: In most cases, authors of Gait & Posture articles did not provide a justification for their study's sample size. The inclusion of the guideline was associated with a modest increase in the percentage of articles providing a justification (16.6-28.1%). A priori power calculations were the dominant type of justification, but many were not reported in enough detail to allow replication.

Significance: Gait & Posture researchers should be more transparent in how they determine their sample sizes and carefully consider if they are suitable. Editors and journals may consider adding a similar guideline as a low-resource way to improve sample size justification reporting.

Keywords: Metascience; Power analysis; Resources; Statistical power; Study design.

MeSH terms

  • Gait*
  • Humans
  • Posture*
  • Research Design
  • Sample Size