IBS is pleased to welcome Dr. Sander Greenland, Emeritus Professor of Epidemiology and Statistics at UCLA as our Keynote Speaker at IBC2024 in Atlanta. It's not too late to register and join us! Visit www.ibc2024.org to get started.
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Toward restoring realism in statistical training and practice
Or, how applied statistics is broken and how we might rebuild it
Sander Greenland, Professor Emeritus
Department of Epidemiology and Department of Statistics
University of California, Los Angeles, California, lesdomes@ucla.edu
Abstract
Cognitive biases are large and unavoidably hardwired into both individual and social
perceptions, yet are overlooked by most methodologic training. Basic statistics originated as a
cognitive aid for preventing hallucination of patterns in noise and for providing reliable
uncertainty assessments. But it spread in a form that encouraged creation of certainty from
ambiguity, which the research community embraced as a core methodology and cultural
tradition.
To deal with this reality, we need to develop and teach methods for seeing and blocking cognitive
biases, as has been done for bias sources like confounding, mismeasurement, and P-selection.
This emergent psychosocial methodology should displace many fine points of traditional
mathematical statistics, which itself is a major source of cognitive biases.
Some background references:
Greenland S. 2017. The need for cognitive science in methodology. Am J Epidemiol 186, 639-
645. https://academic.oup.com/aje/article/186/6/639/3886035
Rafi Z, Greenland S. 2020. Semantic and cognitive tools to aid statistical science: replace
confidence and significance by compatibility and surprise. BMC Med Res Methodol 20, 244.
https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-01105-9
Greenland S. 2022. The causal foundations of applied probability and statistics. Ch. 31 in
Dechter R, Halpern J, Geffner, H., eds. Probabilistic and Causal Inference: The Works of
Judea Pearl. ACM Books no. 36, 605-624, https://arxiv.org/abs/2011.02677
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Courtney Fowler
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