We consider the problem of learning the functions computing children from parents in a Structural Causal Model once the underlying causal graph has been identified. This is in some sense the second step after causal discovery. Taking a probabilistic approach to estimating these functions, we derive a natural myopic active learning scheme that identifies the intervention which is optimally infor...

In this paper, we apply a recently developed differential approach to inference in staged tree models to causal inference. Staged trees generalise modelling techniques established for Bayesian networks (BN). They have the advantage that they can depict highly nuanced structure impossible to express in a BN and also enable us to perform causal manipulations associated with very general types of ...

Health information technology evaluators need to distinguish between intervention efficacy as assessed in the ideal circumstances of clinical trials and intervention effectiveness as assessed in the real world circumstances of actual practice. Because current evaluation study designs do not routinely allow for this distinction, we have developed a framework for evaluation of implementation fide...

New statistical methods allow discovery of causal models from observational data in some circumstances. These models permit both probabilistic inference and causal inference for models of reasonable size. Many domains, such as education, can benefit from such methods. Educational research does not easily lend itself to experimental investigation. Research in laboratories is artificial and poten...

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...

We address the problem of deciding whether a causal or probabilistic query is estimable from data corrupted by missing entries, given a model of missingness process. We extend the results of Mohan et al. [2013] by presenting more general conditions for recovering probabilistic queries of the form P (y|x) and P (y, x) as well as causal queries of the form P (y|do(x)). We show that causal queries...

in order to study the primary inoculum source, apothecium production, as well as overwintering of monilinia laxa, the causal agent of sweet cherry brown rot, this study was carried out in guilan province during 2005-2006. apothecium production by the fungus was investigated under natural and laboratory conditions. the mummified fruits collected in early october didn't produce apothecia und...

causal prepositions по and из-зa in russian language are used for theexpression of undesirable or inconvenient facts and conditions and carrynegative charge and connotation. however, their usage requires differentgrammatical structures. moreover, they are used with different nouns.therefore, the sublties invovlved in some similar cases of the usage of theseprepositions for the expression of cau...