Correcting prevalence estimation for biased sampling with testing errors.

Zhou, Lili; Díaz-Pachón, Daniel Andrés; Zhao, Chen; Rao, J Sunil; Hössjer, Ola

Zhou, Lili; Díaz-Pachón, Daniel Andrés; Zhao, Chen; Rao, J Sunil; Hössjer, Ola.

Afiliação

Zhou L; Division of Biostatistics, University of Miami, Miami, Florida, USA.
Díaz-Pachón DA; Division of Biostatistics, University of Miami, Miami, Florida, USA.
Zhao C; Division of Biostatistics, University of Miami, Miami, Florida, USA.
Rao JS; Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USA.
Hössjer O; Department of Mathematics, Stockholm University, Stockholm, Sweden.

Stat Med ; 42(26): 4713-4737, 2023 Nov 20.

Article em En | MEDLINE | ID: mdl-37655557

Palavras-chave

COVID-19; active information; bias correction; maximum entropy; prevalence; sampling; sampling bias; testing errors

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prevalence_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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