More Power for Less Money: Statistical, Power, and Cost Analyses That Account for Intracluster Correlation in Experiments with Same-Group Cage Mates.

Abstract

In experiments with cohoused animals, outcome variables can become correlated among cage mates. This is called intracluster correlation. When cage mates are all of the same group, the experiment is similar to a cluster randomized trial in human studies. Intracluster correlation in same-group cage mate experiments is a type of pseudoreplication, and ignoring it in statistical analyses increases false-positive results. Herein, we provide a tutorial on how to account for intracluster correlation in statistical analyses. Specifically, this is done by including cage identifiers as an independent variable in a linear mixed model, a type of ANOVA. Because power analyses must be based on the planned statistical analyses, we also include effect size calculations and sample size calculations (types of power analyses) in the tutorial. Effect size and sample size calculations help assure regulatory committees, such as IACUCs, granting agencies, and journals, that experiments are properly powered. These calculations will show that designing experiments to have more cages and fewer animals per cage is more efficient than fewer cages with more animals per cage. This statistical efficiency, which means more power, can be translated into reduced animal numbers, one of the 3Rs (replace, reduce, refine) of animal research. We then perform cost analyses and show how the costs of more cages with fewer animals overall are often less expensive than the costs of fewer cages with more animals overall. Altogether, accounting for intracluster correlation in the experiment design and analysis of same-group cage mate experiments results in fewer statistical errors, reduced costs, and fewer animals. Finally, analyses are demonstrated using JASP, a free, open-source, user-friendly statistical software, and provide R and SAS code to perform the analyses.