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Updated: Mar 29, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
Sequential biases in accumulating evidence
Elena Kulinskaya1, Richard Huggins2, Samson Henry Dogo3
1School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK. e.kulinskaya@uea.ac.uk.
Abstract:
Whilst it is common in clinical trials to use the results of tests at one phase to decide whether to continue to the next phase and to subsequently design the next phase, we show that this can lead to biased results in evidence synthesis. Two new kinds of bias associated with accumulating evidence, termed 'sequential decision bias' and 'sequential design bias', are identified. Both kinds of bias are the result of making decisions on the usefulness of a new study, or its design, based on the previous studies. Sequential decision bias is determined by the correlation between the value of the current estimated effect and the probability of conducting an additional study. Sequential design bias arises from using the estimated value instead of the clinically relevant value of an effect in sample size calculations. We considered both the fixed-effect and the random-effects models of meta-analysis and demonstrated analytically and by simulations that in both settings the problems due to sequential biases are apparent. According to our simulations, the sequential biases increase with increased heterogeneity. Minimisation of sequential biases arises as a new and important research area necessary for successful evidence-based approaches to the development of science. © 2015 The Authors. Research Synthesis Methods Published by John Wiley & Sons Ltd.
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