-
作者：Lysy, Martin; Pillai, Natesh S.; Hill, David B.; Forest, M. Gregory; Mellnik, John W. R.; Vasquez, Paula A.; McKinley, Scott A.
作者单位：University of Waterloo; Harvard University; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of South Carolina System; University of South Carolina Columbia; Tulane University
摘要：State-of-the-art techniques in passive particle-tracking microscopy provide high-resolution path trajectories of diverse foreign particles in biological fluids. For particles on the order of 1 mu m diameter, these paths are generally inconsistent with simple Brownian motion. Yet, despite an abundance of data confirming these findings and their wide-ranging scientific implications, stochastic modeling of the complex particle motion has received comparatively little attention. Even among posited...
-
作者：Yee, Thomas W.
作者单位：University of Auckland
-
作者：Trippa, Lorenzo; Parmigiani, Giovanni
作者单位：Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard T.H. Chan School of Public Health
-
作者：Minsker, Stanislav; Zhao, Ying-Qi; Cheng, Guang
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：Individualized treatment rules (ITRs) tailor treatments according to individual patient characteristics. They can significantly improve patient care and are thus becoming increasingly popular. The data collected during randomized clinical trials are often used to estimate the optimal ITRs. However, these trials are generally expensive to run, and, moreover, they are not designed-to efficiently estimate ITRs. In this article, we propose a cost-effective estimation method from an active learning...
-
作者：Zhou, Bo; Moorman, David E.; Behseta, Sam; Ombao, Hernando; Shahbaba, Babak
作者单位：University of California System; University of California Irvine
摘要：The goal of this article is to develop a novel statistical model for studying cross-neuronal spike train interactions during decision-making. For an individual to successfully complete the task of decision-making, a number of temporally organized events must occur: stimuli must be detected, potential outcomes must be evaluated, behaviors must be executed or inhibited, and outcomes (such as reward or no-reward) must be experienced. Due to the complexity of this process, it is likely the case th...
-
作者：Blei, David M.
作者单位：Columbia University; Columbia University
-
作者：Chen, Guanhua; Zeng, Donglin; Kosorok, Michael R.
作者单位：Vanderbilt University; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
摘要：In dose-finding clinical trials, it is becoming increasingly important to account for individual-level heterogeneity while searching for optimal doses to ensure an optimal individualized dose rule (IDR) maximizes the expected beneficial clinical outcome for each individual. In this article, we advocate a randomized trial design where candidate dose levels assigned to study subjects are randomly chosen from a continuous distribution within a safe range. To estimate the optimal IDR using such da...
-
作者：Diggle, Peter J.; Giorgi, Emanuele
作者单位：Lancaster University
-
作者：Moraga, Paula
作者单位：University of London; London School of Hygiene & Tropical Medicine
-
作者：Roberts, Margaret E.; Stewart, Brandon M.; Airoldi, Edoardo M.
作者单位：University of California System; University of California San Diego; Princeton University; Harvard University
摘要：Statistical models of text have become increasingly popular in statistics and computer science as a method of exploring large document collections. Social scientists often want to move beyond exploration, to measurement and experimentation, and make inference about social and political processes that drive discourse and content. In this article, we develop a model of text data that supports this type of substantive research. Our approach is to posit a hierarchical mixed membership model for an...
