Causal Inference in Oncology Comparative Effectiveness Research Using Observational Data: Are Instrumental Variables Underutilized? The following represents disclosure information provided by authors ...

Setodji CM, McCaffrey DF, Burgette LF, Almirall D, Griffin BA. The right tool for the job: Choosing between covariate balancing and generalized boosted model propensity scores. Epidemiology. 2017.

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 ...

Company will showcase scientific leadership with three key presentations and highlights scalable, data-agnostic research solutions at ISPE Annual Conference 2025. With a strong emphasis on causal ...

This is a preview. Log in through your library . Abstract Understanding the population-level effects of vaccines has important public health policy implications. Inferring vaccine effects from an ...

A Perspective published in Volume 3 of the journal Psychoradiology, researchers from Shanghai Jiao Tong University confronted these challenges and advocates for more clarity and transparency in causal ...

We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...

Hypertension is among the leading cardiovascular diseases. Despite extensive research, evidence concerning the relationship between long-term exposure to ambient particulate matter and hypertension ...