Getting over ANOVA: Estimation graphics for multi-group comparisons

bioRxiv (Cold Spring Harbor Laboratory) 2026 Preprint Open access

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Authors: Zinan Lu, Jonathan Anns, Yishan Mai, Rou Zhang, Kahseng Lian, Nicole MynYi Lee, Shan Hashir, Lucas Wang Zhuoyu, Yixuan Li, A. Rosa Castillo Gonzalez, Joses Wei Hao Ho, Hyungwon Choi
+2 more Sangyu Xu, Adam Claridge‐Chang
DOI: 10.64898/2026.01.26.701654
Cited by: 3
References: 38

Abstract

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.

Fields of Study & Subjects

Meta-analysis and systematic reviews Statistical Methods in Clinical Trials Advanced Causal Inference Techniques

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
27 January 2026
Document type
Preprint