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Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). Biological gradient (dose–response relationship): Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of ...
Correlations must first be confirmed as real, and every possible causative relationship must then be systematically explored. In the end, correlation alone cannot be used as evidence for a cause-and-effect relationship between a treatment and benefit, a risk factor and a disease, or a social or economic factor and various outcomes.
Causation refers to the existence of "cause and effect" relationships between multiple variables. [1] Causation presumes that variables, which act in a predictable manner, can produce change in related variables and that this relationship can be deduced through direct and repeated observation. [2]
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 social sciences and economics. [3]
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.
In Part III, section XV of his book A Treatise of Human Nature, Hume expanded this to a list of eight ways of judging whether two things might be cause and effect. The first three: "The cause and effect must be contiguous in space and time." "The cause must be prior to the effect." "There must be a constant union betwixt the cause and effect.
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.
Causal research, is the investigation of (research into) cause-relationships. [1] [2] [3] To determine causality, variation in the variable presumed to influence the difference in another variable(s) must be detected, and then the variations from the other variable(s) must be calculated (s).