Inferring causality is necessary to achieve the goal of epidemiology, which is to elucidate the cause of disease. Causal inference is conducted in three steps: evaluation of validity of the study, inference of general causality, and inference of individual causality. To evaluate validity of the study, we propose a checklist that focuses on biases and generalizability. For general causal inferen...

causality; concurrency; event structures; frames; locale theory; geometric logic The conventional approach to causality is based on partial orders. Without additional structure, partial orders are only capable of expressing AND causality. In this paper we investigate a syntactic, or logical, approach to causality which allows other causal relationships, such as OR causality, to be expressed wit...

This paper introduces the concept of homogeneous non-causality in heterogeneous panels. This concept is used to examine a panel of data for evidence of a causal relationship between GDP and carbon emissions. The technique is compared to the standard test for homogeneous non-causality in homogeneous panels and heterogeneous non-causality in heterogeneous panels. In North America, Asia and Oceani...