scholarly journals Least-informative priors for 0νββ decay searches

2021 ◽  
Vol 104 (5) ◽  
Author(s):  
Frank F. Deppisch ◽  
Graham Van Goffrier
Keyword(s):  
2018 ◽  
Vol 13 (11) ◽  
pp. 2643-2663 ◽  
Author(s):  
Areti Tsigkinopoulou ◽  
Aliah Hawari ◽  
Megan Uttley ◽  
Rainer Breitling

2021 ◽  
Author(s):  
Bilal Fouad Barakat ◽  
Ameer Dharamshi ◽  
Leontine Alkema ◽  
Manos Antoninis

Estimating school completion is crucial for monitoring SDG 4 on education, and unlike enrollmentindicators, relies on household surveys. Associated data challenges include gaps between waves, conflictingestimates, age misreporting, and delayed completion. Our Adjusted Bayesian Completion Rates (ABC)model overcomes these challenges to produce the first complete and consistent time series for SDGindicator 4.1.2, by school level and sex, for 153 countries. A latent random walk process for unobservedtrue rates is adjusted for a range of error and variance sources, with weakly informative priors. The modelappears well-calibrated and offers a meaningful improvement in predictive performance.


Author(s):  
Vibhu Parcha ◽  
Brittain F. Heindl ◽  
Peng Li ◽  
Rajat Kalra ◽  
Nita A. Limdi ◽  
...  

Background: Among patients receiving percutaneous coronary intervention (PCI), the role of a genotype-guided approach for antiplatelet therapy compared with usual care is unclear. We conducted a Bayesian analysis of the entire TAILOR-PCI (Tailored Antiplatelet Initiation to Lessen Outcomes Due to Decreased Clopidogrel Response After Percutaneous Coronary Intervention) randomized clinical trial population to evaluate the effect of the genotype-guided antiplatelet therapy post-PCI compared with the usual care on the risk of major adverse cardiovascular events (MACE). Methods: The primary outcome for our study was the composite of MACE (myocardial infarction, stroke, and cardiovascular death). Secondary outcomes included cardiovascular death, stroke, myocardial infarction, stent thrombosis, and major/minor bleeding. Bayesian modeling was used to estimate the probability of clinical benefit of genotype-guided therapy using (1) noninformative priors (ie, analyzing the TAILOR-PCI trial) and (2) informative priors derived from the ADAPT, POPular Genetics, IAC-PCI, and PHARMCLO trials (ie, analyzing TAILOR-PCI trial in the context of prior evidence). Risk ratio (RR: ratio of cumulative outcome incidence between genotype-guided and conventional therapy group) and 95% credible interval (CrI) were estimated for the study outcomes, and probability estimates for RR <1 were computed. Results: Using noninformative priors, in TAILOR-PCI the RR for MACE was 0.78 (95% CrI, 0.55–1.07) in genotype-guided therapy after PCI, and the probability of RR <1 was 94%. Using noninformative priors, the probability of RR <1 for cardiovascular death (RR, 0.95 [95% CrI, 0.52–1.74]), stroke (RR, 0.68 [95% CrI, 0.44–1.06]), myocardial infarction (RR, 0.84 [95% CrI, 0.37–1.89]), stent thrombosis (RR, 0.75 [95% CrI, 0.37–1.45]), and major or minor bleeding (RR, 1.22 [95% CrI, 0.84–1.77]) were 57%, 96%, 67%, 94%, and 15%, respectively. Using informative priors, the posterior probability of RR <1 for MACE, from genotype-guided therapy, was 99% (RR, 0.69 [95% CrI, 0.57–0.84]). Using informative priors, the posterior probability of RR <1 for cardiovascular death (RR, 0.86 [95% CrI, 0.61–1.19]), stroke (RR, 0.69 [95% CrI, 0.48–0.99]), myocardial infarction (RR:0.56 [95% CrI, 0.40–0.78]), stent thrombosis (RR, 0.59 [95% CrI, 0.38–0.94]), and major or minor bleeding (RR, 0.84 [95% CrI, 0.70–0.99]) were 81%, 99%, 99%, 99%, and 99%, respectively. Conclusions: Bayesian analysis of the TAILOR-PCI trial provides clinically meaningful data on the posterior probability of reducing MACE using genotype-guided P2Y 12 inhibitor therapy after PCI.


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