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Case Studies in Bayesian Statistics, Volume II by Emery N. Brown, Adam Sapirstein (auth.), Constantine

By Emery N. Brown, Adam Sapirstein (auth.), Constantine Gatsonis, James S. Hodges, Robert E. Kass, Nozer D. Singpurwalla (eds.)

Like its predecessor, this moment quantity offers certain purposes of Bayesian statistical research, each one of which emphasizes the medical context of the issues it makes an attempt to unravel. The emphasis of this quantity is on biomedical purposes. those papers have been provided at a workshop at Carnegie-Mellon college in 1993.

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American Journal of Physiology, 253, H184H193. Buckberg, G. , Luck, J. , Payne, D. , Hoffman, J. , Archie, J. , and Fixler, D. E. (1971). Some sources of error in measuring regional blood flow with radioactive microspheres. Journal of Applied Physiology, 31 (4), 598-604. , Schulz, R, Guth, B. , and Heusch, G, (1991). Measurement of regional myocardial blood flow with multiple colored microspheres. Circulabon, 83, 974-982. 46 Emery N. Brown and Adam Sapirstein RESPONSE TO THE COMMENTS OF PROFESSORS WEISS AND TIBSHIRANI We appreciate the comments and suggestions provided by Professors Weiss and Tibshirani.

Organ Blood Flow Measurement 31 Discussion Robert Tibshirani University of Toronto From both a scientific and statistical point of view, I found this paper a pleasure to read. In my discussion I offer an alternative bootstrap-based analysis, and compare it to the Bayesian analysis carried out by the authors. Interestingly, the two analyses give considerably different results. 1 The Experiment Figure 1 shows a schematic of the experiment.. The objective was to estimate the blood flow Vo into a number of organs in a laboratory rabbit.

In detail, the steps are': 1. Generate x~, ... xj+2 '" Mult(N,p). 2. xj),j = 1, ... J + 1; 1= 1, ... L. 3. Compute '* = Vo ",J '* v.. Jj=l Pj r "* (3) PJ+1 Steps 1-3 are repeated a large number of times B, giving estimates v;l, ... v;B. 3) in Brown and Sapirstein's paper, and using ). * IV;* in place of ). * in steps 2 and 3 above. Non-parametric bootstrap Instead of steps 1 and 2 above, for each segment j we sample CjI" .. cjL with replacement from Cjt, ... CjL. The estimates are then computed as in step 3 above.

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