An example of a complex causal model for managing weight loss, containing both relevant and irrelevant information. When relevant information is not highlighted in the model, participants made poor ...

Objectives The present study was designed to investigate the causal relationships between (time-and strainbased) work-home interference and employee health. The effort-recovery theory provided the ...

Data Poem, a developer of cutting-edge artificial intelligence models for business orchestration, today announced the launch of POEM365, a large causal AI model designed to transform how large ...

Twenty-first century manufacturers post-COVID-19 have been facing significant challenges across their functions in supply chain, risk, operations, and customer experience. Threats by new (often more ...

Causal inference with observational data frequently relies on the notion of the propensity score (PS) to adjust treatment comparisons for observed confounding factors. As decisions in the era of "big ...