Interim analysis is the practice of performing a statistical analysis when the data have only been partially collected, for example, to save resources or to handle the uncertainty of the true effect size. Most statistical designs featuring interim analysis have been developed either in a general statistical setting or for application in clinical trials. As a result, most of them make assumptions and have conditions that in a preclinical setting are usually not met. In this paper, we present necessary changes to the most common forms of interim analysis enhanced for animal experiments, specifically for the t-test and the one-way ANOVA. Finally, we present software that allows freeware use to serve the research community to facilitate the design of experiments featuring interim analyses. The app can be found at It is in the public domain and its code can be found on In this GitHub folder, one can also find a tutorial for the app.

Originele taal-2English
Pagina's (van-tot)248-254
Aantal pagina's7
TijdschriftResearch in Veterinary Science
StatusPublished - jul 2022

Bibliografische nota

Funding Information:
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Publisher Copyright:
© 2022 Elsevier Ltd

Copyright 2022 Elsevier B.V., All rights reserved.


Duik in de onderzoeksthema's van 'Group sequential designs for in vivo studies: Minimizing animal numbers and handling uncertainty in power analysis'. Samen vormen ze een unieke vingerafdruk.

Citeer dit