All of the following are important criteria when making causal inferences except: Select one: a. Predictive value b. Dose-response relationship Incorrect c. Strength of association d. Consistency of association in several studies e. Consistency with existing knowledge
Answer: a. Predictive value
The process of conclusion of the causal connection based on the conditions of the occurrence of an effect is known as Causal inference. Causal inference is a very good example of causal reasoning. Inferring of cause and effect is done in it.
The predictive inference is related to comparisons between units. Positive predictive is the chance of the subjects with positive screening test truly have the disease. Negative predictive value is the chance of the subjects with a negative screening test actually don't have the disease.
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