Qian Guan

Works (4)

Updated: August 19th, 2024 12:40

2021 article

A spatiotemporal recommendation engine for malaria control

Guan, Q., Reich, B. J., & Laber, E. B. (2021, March 20). Biostatistics, Vol. 4.

By: Q. Guan n, B. Reich n  & E. Laber n

Contributors: Q. Guan n, B. Reich n  & E. Laber n

author keywords: Infectious disease; Malaria; Resource allocation; Sequential optimization; Satiotemporal model
MeSH headings : Bayes Theorem; Humans; Malaria / prevention & control; Resource Allocation
topics (OpenAlex): Malaria Research and Control; HIV Research and Treatment; Mosquito-borne diseases and control
TL;DR: The estimated optimal policy under the proposed framework improves the cumulative long-term outcome compared with naive approaches in both simulation experiments and application to malaria interventions in the Democratic Republic of the Congo. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: March 28, 2022

2021 journal article

SMIM: A unified framework of survival sensitivity analysis using multiple imputation and martingale

Biometrics, 79(1), 230–240.

By: S. Yang n , Y. Zhang *, G. Liu * & Q. Guan*

author keywords: delta adjustment; jump-to-reference; restrictive mean survival time; restrictive mean time loss; wild-bootstrap
MeSH headings : Models, Statistical; Computer Simulation; Survival Analysis; Research Design
topics (OpenAlex): Statistical Methods and Inference; Statistical Methods and Bayesian Inference; Statistical Methods in Clinical Trials
TL;DR: A unified framework for sensitivity analysis to censoring at random in survival data using multiple imputation and martingale, called SMIM, is proposed and the wild bootstrap inference has a theoretical guarantee for consistency and is computationally efficient compared to the nonparametric bootstrap counterpart. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID, Crossref
Added: October 4, 2021

2019 article

Bayesian Nonparametric Policy Search With Application to Periodontal Recall Intervals

Guan, Q., Reich, B. J., Laber, E. B., & Bandyopadhyay, D. (2019, September 12). Journal of the American Statistical Association.

By: Q. Guan n, B. Reich n , E. Laber n & D. Bandyopadhyay *

Contributors: Q. Guan n, B. Reich n , E. Laber n & D. Bandyopadhyay *

author keywords: Dirichlet process prior; Dynamic treatment regimes; Observational data; Periodontal disease; Practice-based setting; Precision medicine; Sequential optimization
topics (OpenAlex): Bayesian Methods and Mixture Models; Statistical Methods and Bayesian Inference; Statistical Methods and Inference
TL;DR: Simulation experiments and application to a rich database of electronic dental records from the HealthPartners HMO shows that the proposed method leads to better dental health without increasing the average recommended recall time relative to competing methods. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: October 28, 2019

2016 journal article

Bayesian nonparametric estimation for dynamic treatment regimes with sequential transition times comment

Journal of the American Statistical Association, 111(515), 936–942.

By: Q. Guan, E. Laber & B. Reich 

Source: NC State University Libraries
Added: August 6, 2018

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