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Tirusew Asefa, Ph.D., P.E., BC.WRE., F.ASCE
Tirusew Asefa, Ph.D., P.E., BC.WRE., F.ASCE @TirusewAsefa ·
Sharing our recent paper on "Interpretable hierarchical Bayesian modeling" for monthly stream flow forecast in #Tampa Bay area. Below is the free link for the next 50 days. The idea of #Bayesian hierarchical model is to leverage data at different scales (both in time and information at higher scales (larger watershed, #basin or even #country) and also have more granular information at lower spatial or temporal scale that feeds into the bigger picture that you want to model and understand. Many #Ethiopian basins and the larger #Nile basin can be framed within this framework. If anyone is interested in pursuing this approach to their locality, feel free to reach out and happy to share our codes and the example in this study as well. kwnsfk27.r.eu-west-1.awstrack.me/L0/https:%2F%2…
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ᴅʀ ᴍɪʀᴄᴇᴀ ᴢʟᴏᴛᴇᴀɴᴜ 🌺🌞🍃
ᴅʀ ᴍɪʀᴄᴇᴀ ᴢʟᴏᴛᴇᴀɴᴜ 🌺🌞🍃 @mzloteanu ·
#statstab #514 A puzzle of proportions Thoughts: "Two popular Bayesian tests can yield dramatically different conclusions" Model specification is important. #bayesian #bayes #bayesfactor #nulleffects #proportions doi.org/10.1002/sim.92…
A puzzle of proportions: Two popular Bayesian tests can yield dramatically different conclusions

Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In these domains, it is crucial to be able to quantify evidence for the absence of...

From onlinelibrary.wiley.com
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Haiyan Zheng
Haiyan Zheng @haiyan_zheng ·
Covariate adjustment using GLMs is widely accepted and guided by industry standards. Considerations are yet to extend to basket trials. We explored this by ANCOVA estimators under a #Bayesian hierarchical model, with key results published recently: doi.org/10.1002/sim.70…
Covariate Adjustment in Basket Trials Borrowing Information Across Subgroups

Basket trials are an efficient approach to simultaneously evaluate a single therapy across multiple diseases where patients share a common molecular target. Bayesian hierarchical models (BHMs) are...

From onlinelibrary.wiley.com
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Jame James
Jame James @JamesOrionRpt ·
JOR Bayesian Fusion web application now available. Implements SOP/NHP probabilistic framework Tested across 40+ historical UAP cases. Web app: jamesorion6869.github.io/jor-fusion-web Code: github.com/jamesorion6869… Report: doi.org/10.5281/zenodo… #UAP #Bayesian #DataAnalysis #DefenseTech
GitHub - jamesorion6869/JOR_Framework_PyMC: PyMC implementation of the James Orion Report (JOR)...

PyMC implementation of the James Orion Report (JOR) framework for UAP analysis. - jamesorion6869/JOR_Framework_PyMC

From github.com
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Akhtar Sherin
Akhtar Sherin @academia_kmu ·
Important & timely perspective. As #Bayesian methods gain ground in trials, transparent reporting of prior influence & parallel analyses without informative #priors are essential to safeguard objectivity & trust in results. #ClinicalTrials #BayesianAnalysis
JAMA JAMA @JAMA_current ·
What does the FDA guidance on Bayesian analysis mean for clinical trials? Leading statisticians weigh in: 🧵 💬 Perspective: FDA recommends transparent quantification of prior influence in bayesian analyses and regular supplementary analyses without informative priors tja.ma/4lMqgwbuy
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Jose Tapia
Jose Tapia @TapiaJC1 ·
. @US_FDA #Bayesian methods are promising in oncology. Potentially helpful for analysing composite outcomes frequently used in the curative-intent/peri-operative setting (e.g. DFS, RFS, pCR, MCR, MFS, etc). They can also help address proportional hazard challenges in global RCTs - supporting not only flexible but efficient #ClinicalTrials. Listen 👇 #statistics #rct
Frank Harrell Frank Harrell @f2harrell ·
Thrilled to be interviewed by imminent cardiologist and clinical trialist Mike Gibson yesterday about the new draft Bayesian guidance at FDA: clinicaltrialresults.org/dr-frank-harre… #Statistics #bayes #pharma #clinicaltrials #rct @CMichaelGibson
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