Medical information is judged using only two labels: 'significant' and 'not significant'.However, the actual causal relationship is not hidden there. Beyond statistical significance, there lies a ...

The medical journal article you read last year might actually have been hallucinating. More precisely, the associations the authors assumed were 'causal relationships' might actually be nothing more ...

In a perspective published in Psychoradiology, researchers from Shanghai Jiao Tong University confronted causal inference in clinical neuroscience research and advocate for more clarity and ...

Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...

While econometrics and statistics drove modern quasi-experimental methods for causal inference in policy evaluation, public ...

The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as ...

This paper describes threats to making valid causal inferences about pandemic impacts on student learning based on cross-year comparisons of average test scores. The paper uses Spring 2021 test score ...

Causal inference has transformed empirical political science. Experiments, natural experiments, instrumental variables, difference-in-differences designs, ...