A1 Journal article (refereed)
Estimation of causal effects with small data in the presence of trapdoor variables (2021)
Helske, J., Tikka, S., & Karvanen, J. (2021). Estimation of causal effects with small data in the presence of trapdoor variables. Journal of the Royal Statistical Society. Series A: Statistics in Society, 184(3), 1030-1051. https://doi.org/10.1111/rssa.12699
JYU authors or editors
Publication details
All authors or editors: Helske, Jouni; Tikka, Santtu; Karvanen, Juha
Journal or series: Journal of the Royal Statistical Society. Series A: Statistics in Society
ISSN: 0964-1998
eISSN: 1467-985X
Publication year: 2021
Publication date: 19/05/2021
Volume: 184
Issue number: 3
Pages range: 1030-1051
Publisher: Wiley-Blackwell
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1111/rssa.12699
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/75873
Publication is parallel published: https://arxiv.org/abs/2003.03187
Abstract
We consider the problem of estimating causal effects of interventions from observational data when well-known back-door and front-door adjustments are not applicable. We show that when an identifiable causal effect is subject to an implicit functional constraint that is not deducible from conditional independence relations, the estimator of the causal effect can exhibit bias in small samples. This bias is related to variables that we call trapdoor variables. We use simulated data to study different strategies to account for trapdoor variables and suggest how the related trapdoor bias might be minimized. The importance of trapdoor variables in causal effect estimation is illustrated with real data from the Life Course 1971–2002 study. Using this data set, we estimate the causal effect of education on income in the Finnish context. Bayesian modelling allows us to take the parameter uncertainty into account and to present the estimated causal effects as posterior distributions.
Keywords: Bayesian analysis; estimating (statistical methods); causality
Free keywords: Bayesian estimation; bias; causality; functional constraint; identifiability
Contributing organizations
Related projects
- Competitive funding to strengthen universities’ research profiles. Profiling actions at the JYU, round 3
- Hämäläinen, Keijo
- Research Council of Finland
Ministry reporting: Yes
Reporting Year: 2021
JUFO rating: 2