Abstract
Suppose there are two events that can occur sometime in the future, which we will denote by the letters A and B. For instance, A might be the event that a patient will have his or her blood pressure lowered to “normal” by the treatment about to be given, and B is the event that the patient will remain free from stroke after five years of treatment. We can think of the events by themselves and talk about the probability of each, symbolized
or we can consider the probabilities associated with their relationship. Suppose we can lower the patient’s blood pressure with treatment. Then we might expect that the probability of event B is different than if we had failed to lower the blood pressure. We might expect that the probability of event B, given that A has occurred, symbolized
will be greater than unconditional Prob{B}.
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© 1992 Springer-Verlag New York, Inc.
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Salsburg, D.S. (1992). Bayesian Estimation. In: The Use of Restricted Significance Tests in Clinical Trials. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4414-1_12
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DOI: https://doi.org/10.1007/978-1-4612-4414-1_12
Publisher Name: Springer, New York, NY
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