نتایج جستجو برای: causal process
تعداد نتایج: 1366962 فیلتر نتایج به سال:
A key question in Information Systems research is how information technology creates business value. In this paper, our aim is to help reveal the role of alignment between IT and business resources in business value creation. In particular, we propose that the contribution of IT to business process performance should be investigated in the context of actual IT usage, with IT business alignment ...
Established guidelines for causal inference in epidemiological studies may be inappropriate for genetic associations. A consensus process was used to develop guidance criteria for assessing cumulative epidemiologic evidence in genetic associations. A proposed semiquantitative index assigns three levels for the amount of evidence, extent of replication, and protection from bias, and also generat...
Process algebraic specification languages, i.e., CSP, CCS, LOTOS, etc., are semantically founded in the notion of interleaved traces of events. Unfortunately such traces are inadequate when the dimension of “real” time is considered since a totally ordered trace cannot model two or more time-consuming events overlapping in time. As a first step towards solving this problem, it is explained how,...
This Technical Report includes a causal-based modelling of software measurement processes in order to clarify the real situations in the software metrics application field. A first overview about existing semantic network approaches shows the problems and possible benefits using these formal techniques in the software engineering area. The definition and extension of the causal modelling using ...
We describe an approach to learning causal models that leverages temporal information. We posit the existence of a graphical description of a causal process that generates observations through time. We explore assumptions connecting the graphical description with the statistical process and what one can infer about the causal structure of the process under these assumptions.
The goal of this paper is to reinvestigate the role of causality in probabilistic modeling. We do this based on the observation that causal information is inherently information about probabilistic processes. For instance, if one says that smoking causes cancer, then this means that the act of having a cigarette will initiate some sequence of events within the human body, and that one of the po...
This paper presents a causal simulation method for incompletely known dynamic systems in process engineering . The causal model of a process is represented as both a causal network of interacting elementary dynamic systems, called qualitative automata, influencing one another, and a set of qualitative constraints linking possibly several of such automata . Associated with each influence is a we...
In this paper we provide a formal account of how information about causal processes (i.e., knowledge of the causal chain linking an explanatory variable to an outcome variable) can be used to sharpen causal inferences. All of this is done within a Bayesian potential outcomes causal model. The methods discussed in this paper empower researchers by providing them with a richer palette of causal a...
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