Posterior odds ratios for selected regression hypotheses

Elías Moreno,Francisco José Vázquez-Polo, Miguel Ángel Negrín-Hernández, MJ Al, BA Van Hout, M Allais, J Alonso,L Prieto, JM Anto,X Badía,M Roset,S Montserrat, M Herdman, S Segura, G Baio, A Berardi, A Heath, D Barry, A Hartigan, MS Bartlett, T Bayes, I Bebu, T Mathew, JM Lachin,JO Berger, LR Pericchi,JO Berger, LR Pericchi, JM Bernardo,JO Berger,AP Dawid,AFM Smith,JO Berger, LR Pericchi, P Lahiri,JO Berger, B Betró,E Moreno, LR Pericchi, F Ruggeri, G Salinetti, L Wasserman,JO Berger, JM Bernardo, D Sun,JO Berger,MJ Bayarri, LR Pericchi, JM Bernardo,AFM Smith, DK Bhaumik, A Amatya,ST Normand, J Greenhous, E Kaizar, B Neelon, RD Gibbons, J Bjøner, H Keiding, A Bobinac, J van Exel, FH Rutten, WBF Brouwer, A Briggs, M Sculpher, K Claxton, AH Briggs, P Fenn, AH Briggs, AM Gray, AH Briggs, DE Wonderling, CZ Mooney, R Brooks, JM Brophy, L Joseph, T Burns, F Creed, T Fahy, S Thompson, P Tyrer, I White, PL Canner, G Casella,E Moreno, G Casella,E Moreno, G Casella,E Moreno, FJ Girón, K Chaloner, DA Berry, DK Stangl, K Chaloner, FS Rhame, MA Chaudhary, SC Stearns, S Chib, L Jacobi, O Ciani, C Jommi, M Clyde, EI George, M Clyde, G Parmigiani, B Vidakovic, M Collins, N Latimer, G Consonni, L La Rocca, G Consonni, P Veronese, G Consonni,E Moreno, S Venturini, G Consonni, JJ Forster, L La Rocca, G Consonni, D Fouskakis, B Liseo, I Ntzoufras, NJ Cooper, D Spiegelhalter, S Bujkiewicz, P Dequen, AJ Sutton, JM Corcuera, F Giummolè, JE Cornell, CD Mulrow, R Localio, CB Stack, AR Meibohm, E Guallar, SN Goodman, B Cosmi, C Legnani, M Cini, E Favaretto, G Palareti, EM Crowley, C Davies

Bayesian Cost—Effectiveness Analysis of Medical Treatments（2019）

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摘要

In this chapter we enlarge the sampling information considered so far by adding to the data of cost and effectiveness of every patient a set of patient covariates. The covariates indicate certain deterministic physical characteristics of the patient such as age, sex, health status, and semiological variables of the disease. The optimal treatment for the whole patient population is typically suboptimal for subgroups, and hence the adaptation of the cost-effectiveness analysis to this situation is of interest and yields the cost-effectiveness analysis for subgroups. Since the definition of patient subgroups is made in terms of the set of covariates it is important to exclude those covariates that do not have an influence on the disease. This means that for carrying out a cost-effectiveness analysis for subgroups a previous step should be the statistical detection of the influential covariates from the original set of them. A …

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