Casuality aka causation & association

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(Topic 8.4 Statistical inference and hypothesis testing: Conf) HBS108 Mapa Mental sobre Casuality aka causation & association, creado por shirley.ha el 16/09/2013.
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Casuality aka causation & association
  1. Non-casual associations
    1. 1. Chance associations that can occur at random
      1. 2. Artifactual associations that occur through some error or defect in the design or execution of a study.
        1. 3. Indirect associations in which an exposure is associated with an outcome but through a confounding variable.
        2. have ruled out the likelihood of any of these non-causal explanations for an apparent association
          1. one is left with one additional possibility: The association is causal.
            1. can finally accept the evidence from a research article you need to check if the researchers have discussed their significant results in terms of causality.
          2. presence of an association between A and B does not tell you anything at all about:
            1. a) The presence of the causality
              1. b) The direction of causality.
              2. “To show that A has caused B (rather than B causing A, or A and B both being caused by C [a confounder]), you need more than a correlation coefficient” (….or a RR)6. Bradford Hill “tests for causation” are outlined in the box below (
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