We show that there is a general, informative and reliable procedure for discovering causal relations when, for all the investigator knows, both latent variables and selection bias may be at work. Given information about con­ ditional independence and dependence rela­ tions between measured variables, even when latent variables and selection bias may be present, there are sufficient conditions f...

Causal calculus is a tool to express causal effects in the terms of observational probability distributions. The application of causal calculus in the non-parametric form requires only the knowledge of the causal structure. However, some kind of explicit modeling is needed when numeric estimates of the causal effect are to be calculated. In this paper, the estimation of complicated nonlinear ca...

Accurate measurement of the marginal healthcare costs associated with different diseases and health conditions is important, especially for increasingly prevalent conditions such as obesity. However, existing observational study designs cannot identify the causal impact of disease on healthcare costs. This paper explores the possibilities for causal inference offered by Mendelian randomization,...

The purpose of this study is to examine whether reasoners have two cognitive processes, the causal strength and the reliability, and how the processes work in causal judgments. In an experiment, participants’ causal judgments were varied depending on the conditions, which were introduced to activate either one of the two processes, as well as on the cell configurations between causes and effect...

This survey presents some of the main principles involved in discovering causal relations. They belong to a large array of possible assumptions and conditions about causal relations, whose various combinations limit the possibilities of acquiring causal knowledge in different ways. How much and in what detail the causal structure can be discovered from what kinds of data depends on the particul...

According to causal idealism, causation is a product of human mental activity in a world lacking a mind-independent causal relation. The view is historically popular. Collingwood (1938) held that causal questions are essentially epistemological rather than ontological. Russell (1913) held that there was no role for causation in fundamental physics. And insofar as Hume famously took causation to...

Causal Bayes nets capture many aspects of causal thinking that set them apart from purely associative reasoning. However, some central properties of this normative theory routinely violated. In tasks requiring an understanding of explaining away and screening off, subjects often deviate from these principles and manifest the operation of an associative bias that we refer to as the rich-get-rich...

The goal of the present set of studies is to explore the boundary conditions of category transfer in causal learning. Previous research has shown that people are capable of inducing categories based on causal learning input, and often transfer these categories to new causal learning tasks. However, occasionally learners abandon the learned categories and induce new ones. Whereas previously it h...