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.

Afiliación

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 en En | MEDLINE | ID: mdl-33622016

Asunto(s)

Puntaje de Propensión; Adulto; Anciano; Sesgo; Simulación por Computador; Humanos; Persona de Mediana Edad; Método de Montecarlo; Encuestas Nutricionales

Palabras clave

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

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Puntaje de Propensión Tipo de estudio: Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Humans / Middle aged Idioma: En Revista: Stat Med Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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