This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Philosophov, L. V. Search for Related Content PubMed PubMed Citation Articles by Philosophov, L. V. Social Bookmarking                   What's this?

Bayesian Decision Making Based on Measurements Containing Errors

The paper presents a Bayesian approach to the construction of diagnostic and prognostic algorithms, based on the use of several diagnostic factors (tests) in combination. With this approach, the simultaneous use of dichotomous, discrete, categoric, and continuous factors is easy and the resulting algorithms are more efficient than those of other known methods. Moreover, each factor value that is available for use is assumed to represent an estimate (the result of an imperfect measurement) of some (unknown) true value. The proposed method of accounting for measurement errors is advantageous as regards efficiency for users of the algorithm (physicians) if the accuracy of the factor-measurement techniques at their disposal differs from that of the constructor of the algorithm (the scientist). The approach is illustrated by an example, and possible error models and methods of collecting statistical data are discussed. Key words: Bayes' formula; factors; factor measurements; errors of measurement; estimates; decisions; decision efficiency. (Med Decis Making 1990;15:264- 275)

Medical Decision Making, Vol. 15, No. 3, 264-275 (1995)
DOI: 10.1177/0272989X9501500309


CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?