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Besides plausibility, additional factors contribute to our belief that the relationship between an intervention and its effect is indeed causal, such as consistency (across research settings), temporality (effect follows treatment) and biological gradient (dose response relation).
If the mechanism of HIV-associated risk is directly causal, such as greater susceptibility to HCV when HIV infection is already present, then this effect would not be present before HIV infection occurred.
The construct we develop distinguishes between those risk factors that are directly causal, such as ionizing radiation and inherited germ cell defects, those vulnerability factors that extend the time period during which the breast undergoes development, and those contributing factors that increase total hormonal stimulation of the breast.
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Implied causal constructions, such as causal asyndetic constructions (CACs), have not been given much attention in the literature.
(As with any causal relationship, such as the causal link between smoke and fire, an isolated effect does not refer back to its cause, nor does it provide us with information about the nature of the object or event that causes it. If we experience smoke but have never experienced fire, the smoke will tell us nothing about the nature of fire).
These correlations can result from different causal relationships, such as direct or indirect causal effects between traits, or from a common causal parent, or even from a combination of these.
In contrast, they paraphrased indicative causal conditionals primarily by using causal connectives such as 'because' and temporal connectives such as 'when'.
More sophisticated causal models, such as dynamic Bayesian network, are needed to capture these causal relationships.
In addition to causal connectors, some verbs can also be used to explicitly realize causal relationships, such as cause and make.
To determine causal influences among brain regions and more directly assess theoretical anatomical models requires testing of "effective connectivity," with models that embody causal connections such as structural equation modeling (29) or generative models such as dynamic causal modeling (DCM) (30,31).
Causal conjunctions such as because, so, and as a result signal to readers that a causal connection is being made between two discrete events (Meyer and Poon2001; Williams et al.2007).2007
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