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Statistics in Biosciences
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February 3, 2016
Data-adaptive Shrinkage via the Hyperpenalized EM Algorithm
Philip S Boonstra, Jeremy M G Taylor, Bhramar Mukherjee
Statistica Sinica
|
March 18, 2016
A Small-Sample Choice of the Tuning Parameter in Ridge Regression
Philip S Boonstra, Bhramar Mukherjee, Jeremy M G Taylor
Clinical Trials (London, England)
|
January 22, 2021
A modular framework for early-phase seamless oncology trials
Philip S Boonstra, Thomas M Braun, Elizabeth C Chase
The American Statistician
|
August 20, 2025
A Multiple Imputation Approach for the Cumulative Incidence, with Implications for Variance Estimation
Elizabeth C Chase, Philip S Boonstra, Jeremy M G Taylor
Statistics in Medicine
|
December 14, 2023
Modeling basal body temperature data using horseshoe process regression
Elizabeth C Chase, Jeremy M G Taylor, Philip S Boonstra
American Journal of Hematology
|
January 11, 2021
Ruxolitinib in adult patients with secondary hemophagocytic lymphohistiocytosis
Philip S Boonstra, Asra Ahmed, Samuel A Merrill, et al.
Journal of Survey Statistics and Methodology
|
December 31, 2020
Measures of the Degree of Departure from Ignorable Sample Selection
Roderick J A Little, Brady T West, Philip S Boonstra, et al.
Clinical Trials (London, England)
|
December 27, 2023
Optimizing the doses of cancer drugs after usual dose finding
Garth W Strohbehn, Walter M Stadler, Philip S Boonstra, et al.
Journal of the American Medical Informatics Association : JAMIA
|
March 23, 2016
Is the problem list in the eye of the beholder? An exploration of consistency across physicians
John C Krauss, Philip S Boonstra, Anna V Vantsevich, et al.
Ebiomedicine
|
January 14, 2020
TP63 isoform expression is linked with distinct clinical outcomes in cancer
Armand Bankhead, Thomas McMaster, Yin Wang, et al.
Page
of 6
Search research articles
Search
Showing results (11-20 of 58) with videos related to
Sort By:
Page
of 6
Statistics in Biosciences
|
February 3, 2016
Data-adaptive Shrinkage via the Hyperpenalized EM Algorithm
Philip S Boonstra, Jeremy M G Taylor, Bhramar Mukherjee
Statistica Sinica
|
March 18, 2016
A Small-Sample Choice of the Tuning Parameter in Ridge Regression
Philip S Boonstra, Bhramar Mukherjee, Jeremy M G Taylor
Clinical Trials (London, England)
|
January 22, 2021
A modular framework for early-phase seamless oncology trials
Philip S Boonstra, Thomas M Braun, Elizabeth C Chase
The American Statistician
|
August 20, 2025
A Multiple Imputation Approach for the Cumulative Incidence, with Implications for Variance Estimation
Elizabeth C Chase, Philip S Boonstra, Jeremy M G Taylor
Statistics in Medicine
|
December 14, 2023
Modeling basal body temperature data using horseshoe process regression
Elizabeth C Chase, Jeremy M G Taylor, Philip S Boonstra
American Journal of Hematology
|
January 11, 2021
Ruxolitinib in adult patients with secondary hemophagocytic lymphohistiocytosis
Philip S Boonstra, Asra Ahmed, Samuel A Merrill, et al.
Journal of Survey Statistics and Methodology
|
December 31, 2020
Measures of the Degree of Departure from Ignorable Sample Selection
Roderick J A Little, Brady T West, Philip S Boonstra, et al.
Clinical Trials (London, England)
|
December 27, 2023
Optimizing the doses of cancer drugs after usual dose finding
Garth W Strohbehn, Walter M Stadler, Philip S Boonstra, et al.
Journal of the American Medical Informatics Association : JAMIA
|
March 23, 2016
Is the problem list in the eye of the beholder? An exploration of consistency across physicians
John C Krauss, Philip S Boonstra, Anna V Vantsevich, et al.
Ebiomedicine
|
January 14, 2020
TP63 isoform expression is linked with distinct clinical outcomes in cancer
Armand Bankhead, Thomas McMaster, Yin Wang, et al.
Page
of 6