Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility.
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 puta...
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2021-01-01
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doaj-b395c48405114acbb49d6d69d8033a2b2021-07-04T04:30:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01162e024366810.1371/journal.pone.0243668Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility.Neil R SmalheiserElena E GraetzZhou YuJing WangA 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 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.https://doi.org/10.1371/journal.pone.0243668 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Neil R Smalheiser Elena E Graetz Zhou Yu Jing Wang |
spellingShingle |
Neil R Smalheiser Elena E Graetz Zhou Yu Jing Wang Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility. PLoS ONE |
author_facet |
Neil R Smalheiser Elena E Graetz Zhou Yu Jing Wang |
author_sort |
Neil R Smalheiser |
title |
Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility. |
title_short |
Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility. |
title_full |
Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility. |
title_fullStr |
Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility. |
title_full_unstemmed |
Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility. |
title_sort |
effect size, sample size and power of forced swim test assays in mice: guidelines for investigators to optimize reproducibility. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2021-01-01 |
description |
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 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. |
url |
https://doi.org/10.1371/journal.pone.0243668 |
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