Zobrazeno 1 - 10
of 615
pro vyhledávání: '"Heitjan, Daniel"'
Autor:
Chen, Heng, Heitjan, Daniel F.
We present a method to analyze sensitivity of frequentist inferences to potential nonignorability of the missingness mechanism. Rather than starting from the selection model, as is typical in such analyses, we assume that the missingness arises throu
Externí odkaz:
http://arxiv.org/abs/2302.03740
This work demonstrates the ability to produce readily interpretable statistical metrics for model fit, fixed effects covariance coefficients, and prediction confidence. Importantly, this work compares 4 suitable and commonly applied epistemic UQ appr
Externí odkaz:
http://arxiv.org/abs/2211.15888
Autor:
Balagopal, Anjali, Morgan, Howard, Dohopoloski, Michael, Timmerman, Ramsey, Shan, Jie, Heitjan, Daniel F., Liu, Wei, Nguyen, Dan, Hannan, Raquibul, Garant, Aurelie, Desai, Neil, Jiang, Steve
Automatic segmentation of medical images with DL algorithms has proven to be highly successful. With most of these algorithms, inter-observer variation is an acknowledged problem, leading to sub-optimal results. This problem is even more significant
Externí odkaz:
http://arxiv.org/abs/2102.07880
Autor:
Balagopal, Anjali, Morgan, Howard, Dohopolski, Michael, Timmerman, Ramsey, Shan, Jie, Heitjan, Daniel F., Liu, Wei, Nguyen, Dan, Hannan, Raquibul, Garant, Aurelie, Desai, Neil, Jiang, Steve
Publikováno v:
In Artificial Intelligence In Medicine November 2021 121
Predicting Hospital Readmission in Medicaid Patients With COPD Using Administrative and Claims Data.
Publikováno v:
Respiratory Care; May2024, Vol. 69 Issue 5, p541-548, 8p
Autor:
Chen, Heng, Heitjan, Daniel F.
Publikováno v:
International Journal of Biostatistics; May2024, Vol. 20 Issue 1, p57-67, 11p
Publikováno v:
In Contemporary Clinical Trials Communications March 2020 17
Akademický článek
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Publikováno v:
Annals of Applied Statistics 2013, Vol. 7, No. 4, 2062-2080
Estimates of the effects of treatment on cost from observational studies are subject to bias if there are unmeasured confounders. It is therefore advisable in practice to assess the potential magnitude of such biases. We derive a general adjustment f
Externí odkaz:
http://arxiv.org/abs/1401.1683
Autor:
Li, Shuang1 (AUTHOR), Heitjan, Daniel F.2,3 (AUTHOR)
Publikováno v:
Statistics in Biopharmaceutical Research. Jan-Mar2023, Vol. 15 Issue 1, p125-132. 8p.