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Are spatial models advantageous for predicting county-level HIV epidemiology across the United States?

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第一作者： Danielle,Sass

第一单位： University of Illinois at Urbana-Champaign, USA. Electronic address: dsass2@illinois.edu.

作者： Danielle,Sass ^[1] ; Bita Fayaz,Farkhad ^[2] ; Bo,Li ^[2] ; Man-Pui,Sally Chan ^[2] ; Dolores,Albarracín ^[2]

作者单位： University of Illinois at Urbana-Champaign, USA. Electronic address: dsass2@illinois.edu. ^[1] University of Illinois at Urbana-Champaign, USA. ^[2]

关键词 Dynamic bayesian network Generalized estimating equation HIV Prediction Quantile regression Spatial autoregressive model Two-part model

医学主题词 HIV感染(HIV Infections);人类(Humans);Logistic模型(Logistic Models);美国(United States)

DOI 10.1016/j.sste.2021.100436

PMID 34353528

发布时间 2022-08-02

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Spatial and spatio-temporal epidemiology

2021年38卷

100436页

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Spatial and spatio-temporal epidemiology

2021年38卷

100436页

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Are spatial models advantageous for predicting county-level HIV epidemiology across the United States?

Spatial and spatio-temporal epidemiology

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Spatial and spatio-temporal epidemiology

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Are spatial models advantageous for predicting county-level HIV epidemiology across the United States?

Spatial and spatio-temporal epidemiology

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Spatial and spatio-temporal epidemiology

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