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Ishikawa diagrams (also called fishbone diagrams, [1] herringbone diagrams, cause-and-effect diagrams) are causal diagrams created by Kaoru Ishikawa that show the potential causes of a specific event. [2] Common uses of the Ishikawa diagram are product design and quality defect prevention to identify potential factors causing an overall effect ...
Causal notation is notation used to express cause and effect. In nature and human societies, many phenomena have causal relationships where one phenomenon A (a cause) impacts another phenomenon B (an effect). Establishing causal relationships is the aim of many scientific studies across fields ranging from biology [ 1] and physics [ 2] to ...
Causal reasoning. Causal reasoning is the process of identifying causality: the relationship between a cause and its effect. The study of causality extends from ancient philosophy to contemporary neuropsychology; assumptions about the nature of causality may be shown to be functions of a previous event preceding a later one.
In 1995, Jo C. Phelan and Bruce G. Link developed the theory of fundamental causes. This theory seeks to outline why the association between socioeconomic status (SES) and health disparities has persisted over time, [1] particularly when diseases and conditions previously thought to cause morbidity and mortality among low SES individuals have ...
Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. [1][2] The ...
Causality. Causality is an influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is at least partly responsible for the effect, and the effect is at least partly dependent on the cause. [1] The cause of something may also be ...
Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...
Causal model. In metaphysics, a causal model (or structural causal model) is a conceptual model that describes the causal mechanisms of a system. Several types of causal notation may be used in the development of a causal model. Causal models can improve study designs by providing clear rules for deciding which independent variables need to be ...