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Licensed Unlicensed Requires Authentication Published by De Gruyter November 24, 2020

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  • Misrak Gezmu EMAIL logo and C. Jason Liang
From the journal Statistical Communications in Infectious Diseases
https://doi.org/10.1515/scid-2020-0010
Corresponding author: Misrak Gezmu, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, E-mail:
Published Online: 2020-11-24

© 2020 Walter de Gruyter GmbH, Berlin/Boston

From the journal
Statistical Communications in Infectious Diseases
Statistical Communications in Infectious Diseases
Volume 12 Issue s1
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Pre-selected class-level testing of longitudinal biomarkers reduces required multiple testing corrections to yield novel insights in longitudinal small sample human studies
Joint modeling of time-varying HIV exposure and infection for estimation of per-act efficacy in HIV prevention trials
Comparison of empirical and dynamic models for HIV viral load rebound after treatment interruption
Comparison of machine learning methods for predicting viral failure: a case study using electronic health record data
A semiparametric method for the analysis of outcomes during a gap in HIV care under incomplete outcome ascertainment
Errors in multiple variables in human immunodeficiency virus (HIV) cohort and electronic health record data: statistical challenges and opportunities
Challenges in evaluating the use of viral sequence data to identify HIV transmission networks for public health
Evaluating the relative contribution of data sources in a Bayesian analysis with the application of estimating the size of hard to reach populations
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