Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility [post]

Neil Smalheiser, Elena E. Graetz, Zhou Yu, Jing Wang
2020 unpublished
A recent flood of publications has documented serious problems in scientific reproducibility, power, and reporting of biomedical articles, yet scientists persist in their usual practices. Why? We examined a popular and important preclinical assay, the Forced Swim Test (FST) in mice used to test putative antidepressants. Whether the mice were assayed in a naïve state vs. in a model of depression or stress, and whether the mice were given test agents vs. known antidepressants regarded as positive
more » ... controls, the mean effect sizes seen in the experiments were indeed extremely large (1.5 – 2.5 in Cohen's d units); most of the experiments utilized 7-10 animals per group which did have adequate power to reliably detect effects of this magnitude. We propose that this may at least partially explain why investigators using the FST do not perceive intuitively that their experimental designs fall short -- even though proper prospective design would require ~21-26 animals per group to detect, at a minimum, large effects (0.8 in Cohen's d units) when the true effect of a test agent is unknown. Our data provide explicit parameters and guidance for investigators seeking to carry out prospective power estimation for the FST. More generally, altering the real-life behavior of scientists in planning their experiments may require developing educational tools that allow them to actively visualize the inter-relationships among effect size, sample size, statistical power, and replicability in a direct and intuitive manner.
doi:10.31222/osf.io/nszx3 fatcat:v3by42dt6vhvtkhclh2fxkw5ri