Propensity score trimming mitigates bias due to covariate measurement error in inverse probability of treatment weighted analyses: A plasmode simulation.

Conover, Mitchell M; Rothman, Kenneth J; Stürmer, Til; Ellis, Alan R; Poole, Charles; Jonsson Funk, Michele

Conover, Mitchell M; Rothman, Kenneth J; Stürmer, Til; Ellis, Alan R; Poole, Charles; Jonsson Funk, Michele.

Afiliação

Conover MM; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Rothman KJ; RTI Health Solutions, RTI International, Research Triangle Park, North Carolina, USA.
Stürmer T; Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA.
Ellis AR; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Poole C; School of Social Work, North Carolina State University, Raleigh, North Carolina, USA.
Jonsson Funk M; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Stat Med ; 40(9): 2101-2112, 2021 04.

Article em En | MEDLINE | ID: mdl-33622016

Assuntos

Pontuação de Propensão; Adulto; Idoso; Viés; Simulação por Computador; Humanos; Pessoa de Meia-Idade; Método de Monte Carlo; Inquéritos Nutricionais

Palavras-chave

Monte Carlo method; bias; classification; confounding factors; propensity score

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pontuação de Propensão Tipo de estudo: Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Humans / Middle aged Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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