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作者：Huo, Zhiguang; Song, Chi; Tseng, George
作者单位：State University System of Florida; University of Florida; University System of Ohio; Ohio State University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
摘要：Due to the rapid development of high-throughput experimental techniques and fast-dropping prices, many transcriptomic datasets have been generated and accumulated in the public domain. Meta-analysis combining multiple transcriptomic studies can increase the statistical power to detect disease-related biomarkers. In this paper we introduce a Bayesian latent hierarchical model to perform transcriptomic meta-analysis. This method is capable of detecting genes that are differentially expressed (DE...
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作者：Johndrow, James E.; Lum, Kristian
作者单位：Stanford University
摘要：Predictive modeling is increasingly being employed to assist human decision-makers. One purported advantage of replacing or augmenting human judgment with computer models in high stakes settings-such as sentencing, hiring, policing, college admissions, and parole decisions-is the perceived neutrality of computers. It is argued that because computer models do not hold personal prejudice, the predictions they produce will be equally free from prejudice. There is growing recognition that employin...
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作者：Sales, Adam C.; Pane, John F.
作者单位：University of Texas System; University of Texas Austin; RAND Corporation
摘要：Students in Algebra I classrooms typically learn at different rates and struggle at different points in the curriculum-a common challenge for math teachers. Cognitive Tutor Algebra I (CTA1), an educational computer program, addresses such student heterogeneity via what they term mastery learning, where students progress from one section of the curriculum to the next by demonstrating appropriate mastery at each stage. However, when students are unable to master a section's skills even after try...
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作者：Wu, Xiao; Braun, Danielle; Kioumourtzoglou, Marianthi-Anna; Choirat, Christine; Di, Qian; Dominici, Francesca
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Columbia University
摘要：We propose a new approach for estimating causal effects when the exposure is measured with error and confounding adjustment is performed via a generalized propensity score (GPS). Using validation data, we propose a regression calibration (RC)-based adjustment for a continuous error-prone exposure combined with GPS to adjust for confounding (RC-GPS). The outcome analysis is conducted after transforming the corrected continuous exposure into a categorical exposure. We consider confounding adjust...
