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A note on Bahadur's expansion in Bayesian diagnostic algorithms
Get PDFScheinok's (1972) empirical results, obtained from using Bahadur's expansion in Bayes's theorem, are explained by noting that the expansion is an exact representation of observed probabilities and thus no information was gained by its use. The calculated and observed joint probability distributions will always be equal. It is also demonstrated that posterior probabilities equal to the ratio of observed patients with a given profile in a disease category to the total number of patients with the symptom profile are always obtained when actuarial probability estimates are used in Bayes's theorem.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/33902/1/0000167.pd
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