Causal inference on human behaviour

Drew H Bailey¹, Alexander J Jung², Adriene M Beltz³, Markus I Eronen⁴, Christian Gische⁵, Ellen L Hamaker⁶, Konrad P Kording^{7

8}, Catherine Lebel^{9

10}, Martin A Lindquist¹¹, Julia Moeller¹², Adeel Razi^{13

14

15

16}, Julia M Rohrer¹⁷, Baobao Zhang¹⁸, Kou Murayama^{2

19}

Affiliations

¹ School of Education, University of California, Irvine, Irvine, CA, USA. dhbailey@uci.edu.
² Hector Research Institute of Education Sciences and Psychology, University of Tübingen, Tübingen, Germany.
³ Department of Psychology, University of Michigan, Ann Arbor, MI, USA.
⁴ Department of Theoretical Philosophy, University of Groningen, Groningen, the Netherlands.
⁵ Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.
⁶ Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, the Netherlands.
⁷ Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
⁸ Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA.
⁹ Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada.
¹⁰ Department of Radiology, University of Calgary, Calgary, Alberta, Canada.
¹¹ Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.
¹² Leipzig University, Leipzig, Germany.
¹³ Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia.
¹⁴ Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
¹⁵ Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK.
¹⁶ CIFAR Azrieli Global Scholars Program, CIFAR, Toronto, Ontario, Canada.
¹⁷ Wilhelm Wundt Institute for Psychology, Faculty of Life Sciences, Leipzig University, Leipzig, Germany.
¹⁸ Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, NY, USA.
¹⁹ Research Institute, Kochi University of Technology, Kochi, Japan.

PMID: 39179747
DOI: 10.1038/s41562-024-01939-z

Review

Causal inference on human behaviour

Drew H Bailey et al. Nat Hum Behav. 2024 Aug.

. 2024 Aug;8(8):1448-1459.

doi: 10.1038/s41562-024-01939-z. Epub 2024 Aug 23.

Authors

Affiliations

¹ School of Education, University of California, Irvine, Irvine, CA, USA. dhbailey@uci.edu.
² Hector Research Institute of Education Sciences and Psychology, University of Tübingen, Tübingen, Germany.
³ Department of Psychology, University of Michigan, Ann Arbor, MI, USA.
⁴ Department of Theoretical Philosophy, University of Groningen, Groningen, the Netherlands.
⁵ Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.
⁶ Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, the Netherlands.
⁷ Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
⁸ Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA.
⁹ Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada.
¹⁰ Department of Radiology, University of Calgary, Calgary, Alberta, Canada.
¹¹ Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.
¹² Leipzig University, Leipzig, Germany.
¹³ Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia.
¹⁴ Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
¹⁵ Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK.
¹⁶ CIFAR Azrieli Global Scholars Program, CIFAR, Toronto, Ontario, Canada.
¹⁷ Wilhelm Wundt Institute for Psychology, Faculty of Life Sciences, Leipzig University, Leipzig, Germany.
¹⁸ Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, NY, USA.
¹⁹ Research Institute, Kochi University of Technology, Kochi, Japan.

PMID: 39179747
DOI: 10.1038/s41562-024-01939-z

Abstract

Making causal inferences regarding human behaviour is difficult given the complex interplay between countless contributors to behaviour, including factors in the external world and our internal states. We provide a non-technical conceptual overview of challenges and opportunities for causal inference on human behaviour. The challenges include our ambiguous causal language and thinking, statistical under- or over-control, effect heterogeneity, interference, timescales of effects and complex treatments. We explain how methods optimized for addressing one of these challenges frequently exacerbate other problems. We thus argue that clearly specified research questions are key to improving causal inference from data. We suggest a triangulation approach that compares causal estimates from (quasi-)experimental research with causal estimates generated from observational data and theoretical assumptions. This approach allows a systematic investigation of theoretical and methodological factors that might lead estimates to converge or diverge across studies.

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References

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Causal inference on human behaviour

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Causal inference on human behaviour

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