The present investigation examined the temporal relationships between changes in coronary artery heart disease (CAHD) mortality rates from whites (1938-1980) and changes in national measures of dietary elements, tobacco consumption, alcohol consumption, and unemployment. The magnitude and latency of the causal relationships were estimated with the use of cross-lagged correlation functions (CCFs...

The burgeoning interest in the field of epigenetics has precipitated the need to develop approaches to strengthen causal inference when considering the role of epigenetic mediators of environmental exposures on disease risk. Epigenetic markers, like any other molecular biomarker, are vulnerable to confounding and reverse causation. Here, we present a strategy, based on the well-established fram...

Causal inference is often phrased as a missing data problem – for every unit, only the response to observed treatment assignment is known, the response to other treatment assignments is not. In this paper, we extend the converse approach of [7] of representing missing data problems to causal models where only interventions on missingness indicators are allowed. We further use this representatio...

In contrast to statistical methods, a number of case study methods—collectively referred to as Mill’s methods, used by generations of social science researchers—only consider deterministic relationships. They do so to their detriment because heeding the basic lessons of statistical inference can prevent serious inferential errors. Of particular importance is the use of conditional probabilities...