The benign characteristics formerly attributed to Plasmodium vivax infections have recently changed owing to the increasing number of reports of severe vivax malaria resulting in a broad spectrum of clinical complications, probably including undernutrition. Causal inference is a complex process, and arriving at a tentative inference of the causal or non-causal nature of an association is a subj...

How humans infer causation from covariation has been the subject of a vigorous debate, most recently between the computational causal power account (P. W. Cheng, 1997) and associative learning theorists (e.g., K. Lober & D. R. Shanks, 2000). Whereas most researchers in the subject area agree that causal power as computed by the power PC theory offers a normative account of the inductive process...

Recent papers by a number of philosophers have been concerned with the question of whether natural selection is a causal process, and if it is, whether the causes of selection are properties of individuals or properties of populations. I shall argue that much confusion in this debate arises because of a failure to distinguish between causal productivity and causal relevance. Causal productivity...

The reheating process in in ationary universe models is considered as an out-of-equilibrium mixture of two interacting and reacting uids, and studied within the framework of causal, irreversible thermodynamics. The evolution of the temperature and the decay rate as determined by causal thermodynamics are estimated at di erent stages of the process. A simple model is also used to nd the perturba...

Nearly every theory of causal induction assumes that the existence and strength of causal relations needs to be inferred from observational data in the form of covariations. The last few decades have seen much controversy over exactly how covariations license causal conjectures. One consequence of this debate is that causal induction research has taken for granted that covariation information i...

RATIONALE Several frameworks can be used to evaluate decision making. These may relate to different aspects of the decision-making process, or concern the decision outcome. Evaluations of psychodiagnostic decisions have shown diagnosticians to be poor decision makers. In this essay we argue that this finding results from the evaluation of only one part of the diagnostic process. METHOD We put...

Causal learning in childhood is a dynamic and collaborative process of explanation and exploration within complex physical and social environments. Understanding how children learn causal knowledge requires examining how they update beliefs about the world given novel information and studying the processes by which children learn in collaboration with caregivers, educators, and peers. The objec...

Based on the predictions of a computational model, we test preschoolers’ ability to reason about stream location effects: reasoning that interventions that occur on a common part of a causal process should be more likely to affect multiple relations, than interventions which occur on independent parts of a causal process. In two experiments, we show that 3and 4year-olds both show a stream locat...

Maximal Ancestral Graphs (MAGs) are probabilistic graphical models that can model the distribution and causal properties of a set of variables in the presence of latent confounders. They are closed under marginalization. Invariant pairwise features of a class of Markov equivalent MAGs can be learnt from observational data sets using the FCI algorithm and its variations (such as conservative FCI...

Background : Clinical trials in medicine use probability -based statistics. Statistics separate the patient’s physiologic elements (specified as variables when given numeric form) from his or her body and define causal correlation for the group. Diagnostic and clinical decisions at the individual patient level are currently based on these definitions of causation. Because data is grouped and av...