J
Jing Cheng
Researcher at University of California, San Francisco
Publications - 76
Citations - 4012
Jing Cheng is an academic researcher from University of California, San Francisco. The author has contributed to research in topics: Randomized controlled trial & Instrumental variable. The author has an hindex of 27, co-authored 72 publications receiving 2915 citations. Previous affiliations of Jing Cheng include University of Florida & University of Pennsylvania.
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Instrumental variable methods for causal inference
TL;DR: This tutorial discusses the types of causal effects that can be estimated by instrumental variables analysis; the assumptions needed to provide valid estimates of causaleffects and sensitivity analysis for those assumptions; methods of estimation of causal Effects using instrumental variables; and sources of instrumental variables in health studies.
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Transmission, infectivity, and neutralization of a spike L452R SARS-CoV-2 variant.
Xianding Deng,Miguel Garcia-Knight,Mir M. Khalid,Venice Servellita,Candace Wang,Mary Kate Morris,Alicia Sotomayor-Gonzalez,Dustin R. Glasner,Kevin Reyes,Amelia S. Gliwa,Nikitha P. Reddy,Claudia Sanchez San Martin,Scot Federman,Jing Cheng,Joanna Balcerek,Jordan E. Taylor,Jessica Streithorst,Steve Miller,Bharath Sreekumar,Pei-Yi Chen,Ursula Schulze-Gahmen,Taha Y. Taha,Jennifer M. Hayashi,Camille R. Simoneau,G. Renuka Kumar,Sarah McMahon,Peter V. Lidsky,Yinghong Xiao,Peera Hemarajata,Nicole M. Green,Alex Espinosa,Chantha Kath,Monica Haw,John Bell,Jill K. Hacker,Carl L. Hanson,Debra A. Wadford,Carlos Anaya,Donna Ferguson,Phillip A. Frankino,Haridha Shivram,Liana F. Lareau,Stacia K. Wyman,Melanie Ott,Melanie Ott,Raul Andino,Charles Y. Chiu +46 more
TL;DR: In this article, the authors identified an emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant by viral whole-genome sequencing of 2,172 nasal/nasopharyngeal swab samples from 44 counties in California, a state in the western United States.
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Real Longitudinal Data Analysis for Real People: Building a Good Enough Mixed Model
TL;DR: A systematic strategy for addressing the challenge of how to build a good enough mixed effects model is suggested and easily implemented practical advice to build mixed effects models is introduced.
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Association Between Youth Smoking, Electronic Cigarette Use, and COVID-19.
TL;DR: Whether youth cigarette and electronic cigarette use are associated with coronavirus disease 2019 symptoms, testing, and diagnosis and cigarettes only, e-cigarettes only and dual use, sociodemographic factors, obesity, and complying with shelter-in-place is assessed.
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Respirator Tolerance in Health Care Workers
TL;DR: The aim of this work is to contribute to the understanding of why certain types of cancers are more difficult to treat with chemotherapy and the role of these drugs and their role in the development and implementation is to help facilitate that process.