Quantitative Methodologies 2: Confusion bias and how to control a confounding factor

Addressing confounding bias is one of the challenges when conducting causality studies. This occurs when we report a causal association between an exposure and an outcome, when in fact it could be result of the effect of a third factor called confounding variable. That is, when an confounder variabl...

Descripción completa

Detalles Bibliográficos
Autores: Quispe, Antonio M., Alvarez-Valdivia, María Gracia, Loli-Guevara, Silvana
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:Perú
Institución:Cuerpo Médico Hospital Nacional Almanzor Aguinaga Asenjo
Repositorio:Revista del Cuerpo Médico Hospital Nacional Almanzor Aguinaga Asenjo
Idioma:español
OAI Identifier:oai:cmhnaaa.org.pe:article/675
Acceso en línea:https://cmhnaaa.org.pe/index.php/rcmhnaaa/article/view/675
Access Level:acceso abierto
Palabra clave:Sesgo de confusión
Diseño de Investigaciones Epidemiológicas
Sesgos
Análisis de regresión
Puntajes de propensión
Confounding Factors
Epidemiologic
Epidemiologic Research Design
Bias
Regression Analysis
Propensity Score
Descripción
Sumario:Addressing confounding bias is one of the challenges when conducting causality studies. This occurs when we report a causal association between an exposure and an outcome, when in fact it could be result of the effect of a third factor called confounding variable. That is, when an confounder variable creates a spurious relationship between the exposure or independent variable and the outcome of interest or dependent variable. By knowing the confounding variables and their association with the exposure of interest, the confounding bias could be controlled. To control for confounding bias, we can use different methods. These include techniques applied in study design, such as restriction, randomization, and coincidence, and techniques used in data analysis, such as stratification, multivariate analysis, standardization, propensity scores, analysis sensitivity and the inverse probability weighting. In this review, we discuss how to identify a confounding variable and the main techniques for controlling for confounding bias.