Abstract Causal inference with observational data frequently requires researchers to estimate treatment effects … bias than the corresponding reliable measure. Practical implications for causal inference will be discussed.  …

causal inference) methods, some conditions must be satisfied. One requirement is that the outcomes of individuals are not … methods for causal inference even under interference. In this paper, we review some of the most important contributions made …

Randomised controlled or clinical trials (RCTs) are generally viewed as the most reliable method to draw causal … inference as to the effects of a treatment, as they should guarantee that the individuals being compared differ only in terms of … causal model. This ‘no randomisation bias’ assumption is generally untestable but if violated would undermine the causal …