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bioRxiv · 10.64898/2026.01.26.701654

Getting over ANOVA: Estimation graphics for multi-group comparisons

Lu, Z.·Anns, J.·Mai, Y.·Zhang, R.·Lian, K.·Lee, N. M.·Hashir, S.·Wang Zhouyu, L.·Gonzalez, A. R. C.·Ho, J.·Choi, H.·Xu, S.·Claridge-Chang, A.
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Abstract

Data analysis in experimental science mainly relies on null-hypothesis significance testing, despite its well-known limitations. A powerful alternative is estimation statistics, which focuses on effect-size quantification. However, current estimation tools struggle with the complex, multi-group comparisons common in biological research. Here we introduce DABEST 2.0, an estimation framework for complex experimental designs, including shared-control, repeated-measures, two-way factorial experiments, and meta-analysis of replicates.

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Lu, Z., Anns, J., Mai, Y., Zhang, R., Lian, K., Lee, N. M., Hashir, S., Wang Zhouyu, L., Gonzalez, A. R. C., Ho, J., Choi, H., Xu, S., Claridge-Chang, A.. 2026-01-27. Getting over ANOVA: Estimation graphics for multi-group comparisons. https://doi.org/10.64898/2026.01.26.701654

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