Exploring causality from observational data: An example assessing whether religiosity promotes cooperation.

ABSTRACT: Causal inference from observational data is notoriously difficult, and relies upon many unverifiable assumptions, including no confounding or selection bias. Here, we demonstrate how to apply a range of sensitivity analyses to examine whether a causal interpretation from observational data may be justified. These methods include: testing different confounding structures (as the assumed confounding model may be incorrect), exploring potential residual confounding and assessing the impact of selection bias due to missing data. We aim to answer the causal question 'Does religiosity promote cooperative behaviour?' as a motivating example of how these methods can be applied. We use data from the parental generation of a large-scale (n = approximately 14,000) prospective UK birth cohort (

SUBMITTER: Major-Smith D 

PROVIDER: S-EPMC10426067 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature