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- W4319444313 abstract "Advice taking and related research is dominated by deterministic weighting indices, specifically ratio-of-differences-based formulas for investigating informational influence. Their arithmetic is intuitively simple, but they pose several measurement problems and restrict research to a particular paradigmatic approach. As a solution, we propose process-consistent mixed-effects regression modeling to specify how strongly peoples’ judgments are influenced by externally provided evidence. The formal derivation of the proposed weighting measures is accompanied by a detailed elaboration on their most important technical and statistical subtleties. Essentially, by implementing appropriate multilevel models, our approach explicitly distinguishes between components of endogenous (i.e., final judgments) and exogenous nature, such as independent initial judgments and advice. Corresponding mixed-effects regression coefficients of various exogenous sources of information thus also reflect individual weighting, but are based on a conceptually consistent representation of the endogenous judgment process. We use this modeling approach to revisit empirical findings from several paradigms investigating algorithm aversion, sequential collaboration, and advice taking. In summary, we replicate and extend the original finding of algorithm appreciation, and initially demonstrate a lack of evidence for systematic order effects in sequential collaboration or for differential weighting of multiple individual pieces of advice. In addition to opening new avenues for innovative research, process-consistent modeling of information sampling and utilization has the potential to increase the reproducibility and replicability of our science. Furthermore, the proposed method is relevant beyond advice taking, as mixed-effects regression weights can also inform research on related cognitive phenomena such as multidimensional belief updating, anchoring effects, hindsight bias, or attitude change." @default.
- W4319444313 created "2023-02-09" @default.
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- W4319444313 date "2023-02-06" @default.
- W4319444313 modified "2023-09-30" @default.
- W4319444313 title "Mixed-Effects Regression Weights (of Advice): Process-Consistent Modeling of Information Sampling and Utilization" @default.
- W4319444313 doi "https://doi.org/10.31234/osf.io/x36az" @default.
- W4319444313 hasPublicationYear "2023" @default.
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