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We propose a mechanism for copying of neuronal networks that is of considerable interest for neuroscience for it suggests a neuronal basis for causal inference, function copying, and natural selection within the human brain.
Cross-sectional design provides a limited basis for causal inference, especially if there are omitted variables.
Although the latter provide a weaker basis for causal inference, similar econometric evidence supported the initial case for tobacco taxation.
A second limitation of the present study is that it is cross-sectional, so we cannot strengthen the basis for causal inference regarding MSDs.
Case⌓control studies require a considerably smaller sample size than the corresponding longitudinal studies, and is as effective as the cohort study as a basis for causal inference [ 29].
Such evidence for how an intervention achieves its effects (causal explanation) can be combined with the evidence for the size of those effects (causal estimation) to provide a stronger basis for causal inference.
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A second obvious limitation is that our research design cannot be used as the basis for causal inferences.
The present results do not constitute a basis for causal inferences, as superior cognitive control could be present from birth to a higher extent in musicians than in non-musicians, and hence may partly have primed musicians in their successful choice of career.
We review the causal inference problem in social epidemiology, and the potential for causal inference in randomized social interventions.
In this subsection, we discuss a methodology for causal inference in observational data.
However, the value of this association for causal inference is uncertain.
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