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pro vyhledávání: '"Ibrahim, A. G"'
In oncology clinical trials, tumor burden (TB) stands as a crucial longitudinal biomarker, reflecting the toll a tumor takes on a patient's prognosis. With certain treatments, the disease's natural progression shows the tumor burden initially recedin
Externí odkaz:
http://arxiv.org/abs/2409.13873
Autor:
Zhang, Hongtao, Anderson, Keaven M, Zimmer, Zachary, Golm, Gregory, Sapre, Aditi, Ibrahim, Joseph G
With the robust uptick in the applications of Bayesian external data borrowing, eliciting a prior distribution with the proper amount of information becomes increasingly critical. The prior effective sample size (ESS) is an intuitive and efficient me
Externí odkaz:
http://arxiv.org/abs/2404.13366
The BayesPPDSurv (Bayesian Power Prior Design for Survival Data) R package supports Bayesian power and type I error calculations and model fitting using the power and normalized power priors incorporating historical data with for the analysis of time
Externí odkaz:
http://arxiv.org/abs/2404.05118
The power prior is a popular class of informative priors for incorporating information from historical data. It involves raising the likelihood for the historical data to a power, which acts as a discounting parameter. When the discounting parameter
Externí odkaz:
http://arxiv.org/abs/2404.02453
Generalized linear mixed models (GLMMs) are widely used in research for their ability to model correlated outcomes with non-Gaussian conditional distributions. The proper selection of fixed and random effects is a critical part of the modeling proces
Externí odkaz:
http://arxiv.org/abs/2305.08204
Autor:
Heiling, Hillary M., Rashid, Naim U., Li, Quefeng, Peng, Xianlu L., Yeh, Jen Jen, Ibrahim, Joseph G.
Modern biomedical datasets are increasingly high dimensional and exhibit complex correlation structures. Generalized Linear Mixed Models (GLMMs) have long been employed to account for such dependencies. However, proper specification of the fixed and
Externí odkaz:
http://arxiv.org/abs/2305.08201
It is becoming increasingly popular to elicit informative priors on the basis of historical data. Popular existing priors, including the power prior, commensurate prior, and robust meta-analytic prior provide blanket discounting. Thus, if only a subs
Externí odkaz:
http://arxiv.org/abs/2303.05223
The power prior is a popular class of informative priors for incorporating information from historical data. It involves raising the likelihood for the historical data to a power, which acts as discounting parameter. When the discounting parameter is
Externí odkaz:
http://arxiv.org/abs/2302.14230
Publikováno v:
Journal of Computational and Graphical Statistics, 2023
Deep Learning (DL) methods have dramatically increased in popularity in recent years, with significant growth in their application to supervised learning problems in the biomedical sciences. However, the greater prevalence and complexity of missing d
Externí odkaz:
http://arxiv.org/abs/2207.08911
Publikováno v:
In Journal of Industrial and Engineering Chemistry 25 December 2024 140:258-268
