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Using Bounds to Compare the Strength of Exchangeability Assumptions for Internal and External Validity.
Breskin, Alexander; Westreich, Daniel; Cole, Stephen R; Edwards, Jessie K.
Afiliação
  • Breskin A; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
  • Westreich D; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
  • Cole SR; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
  • Edwards JK; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Am J Epidemiol ; 188(7): 1355-1360, 2019 07 01.
Article em En | MEDLINE | ID: mdl-30834430
ABSTRACT
In the absence of strong assumptions (e.g., exchangeability), only bounds for causal effects can be identified. Here we describe bounds for the risk difference for an effect of a binary exposure on a binary outcome in 4 common study settings observational studies and randomized studies, each with and without simple random selection from the target population. Through these scenarios, we introduce randomizations for selection and treatment, and the widths of the bounds are narrowed from 2 (the width of the range of the risk difference) to 0 (point identification). We then assess the strength of the assumptions of exchangeability for internal and external validity by comparing their contributions to the widths of the bounds in the setting of an observational study without random selection from the target population. We find that when less than two-thirds of the target population is selected into the study, the assumption of exchangeability for external validity of the risk difference is stronger than that for internal validity. The relative strength of these assumptions should be considered when designing, analyzing, and interpreting observational studies and will aid in determining the best methods for estimating the causal effects of interest.
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Texto completo: 1 Eixos temáticos: Pesquisa_clinica Base de dados: MEDLINE Assunto principal: Ensaios Clínicos Controlados Aleatórios como Assunto / Métodos Epidemiológicos / Causalidade / Modelos Estatísticos / Estudos Observacionais como Assunto Tipo de estudo: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Eixos temáticos: Pesquisa_clinica Base de dados: MEDLINE Assunto principal: Ensaios Clínicos Controlados Aleatórios como Assunto / Métodos Epidemiológicos / Causalidade / Modelos Estatísticos / Estudos Observacionais como Assunto Tipo de estudo: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article