Bayesian hypothesis testing-use in interpretation of measurements.

by: G Miller, H Martz, T Little, L Bertelli

Health Phys, Vol. 94, No. 3. (March 2008), pp. 248-254.

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Abstract

Bayesian hypothesis testing may be used to qualitatively interpret a dataset as indicating something "detected" or not. Hypothesis testing is shown to be equivalent to testing the posterior distribution for positive true amounts by redefining the prior to be a mixture of the original prior and a delta-function component at 0 representing the null hypothesis that nothing is truly present. The hypothesis-testing interpretation of the data is based on the posterior probability of the usual modeling hypothesis relative to the null hypothesis. Real numerical examples are given and discussed, including the distribution of the non-null hypothesis probability over 4,000 internal dosimetry cases. Currently used comparable methods based on classical statistics are discussed.

@article{citeulike:2491691, abstract = {Bayesian hypothesis testing may be used to qualitatively interpret a dataset as indicating something "detected" or not. Hypothesis testing is shown to be equivalent to testing the posterior distribution for positive true amounts by redefining the prior to be a mixture of the original prior and a delta-function component at 0 representing the null hypothesis that nothing is truly present. The hypothesis-testing interpretation of the data is based on the posterior probability of the usual modeling hypothesis relative to the null hypothesis. Real numerical examples are given and discussed, including the distribution of the non-null hypothesis probability over 4,000 internal dosimetry cases. Currently used comparable methods based on classical statistics are discussed.}, address = {Los Alamos National Laboratory, MS-E546, Los Alamos, NM 87545, USA. guthrie@lanl.gov}, author = {Miller, G. and Martz, H. and Little, T. and Bertelli, L. }, citeulike-article-id = {2491691}, doi = {10.1097/01.HP.0000290624.35701.00}, issn = {0017-9078}, journal = {Health Phys}, keywords = {bayes}, month = {March}, number = {3}, pages = {248--254}, posted-at = {2008-03-09 01:22:25}, priority = {2}, title = {Bayesian hypothesis testing-use in interpretation of measurements.}, url = {http://dx.doi.org/10.1097/01.HP.0000290624.35701.00}, volume = {94}, year = {2008} }

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TY - JOUR ID - citeulike:2491691 L3 - citeulike-article-id:2491691 TI - Bayesian hypothesis testing-use in interpretation of measurements. JF - Health Phys VL - 94 IS - 3 SP - 248 EP - 254 AD - Los Alamos National Laboratory, MS-E546, Los Alamos, NM 87545, USA. guthrie@lanl.gov SN - 0017-9078 N2 - Bayesian hypothesis testing may be used to qualitatively interpret a dataset as indicating something "detected" or not. Hypothesis testing is shown to be equivalent to testing the posterior distribution for positive true amounts by redefining the prior to be a mixture of the original prior and a delta-function component at 0 representing the null hypothesis that nothing is truly present. The hypothesis-testing interpretation of the data is based on the posterior probability of the usual modeling hypothesis relative to the null hypothesis. Real numerical examples are given and discussed, including the distribution of the non-null hypothesis probability over 4,000 internal dosimetry cases. Currently used comparable methods based on classical statistics are discussed. KW - bayes AU - Miller, G AU - Martz, H AU - Little, T AU - Bertelli, L PY - 2008/03// UR - http://dx.doi.org/10.1097/01.HP.0000290624.35701.00 ER -

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