Investigation of the structure and magnitude of time-varying uncontrolled confounding in simulated cohort data analyzed using g-computation

Article Public, Environmental & Occupational Health

Simultaneous adjustment of uncontrolled confounding, selection bias and misclassification in multiple-bias modelling

Paul Brendel et al.

Summary: Traditional multiple-bias adjustment involves adjusting for biases one at a time, while a novel alternative approach is to simultaneously adjust for all biases using imputation and/or regression weighting. A simulation study showed that using correct bias parameters can yield unbiased effect estimates, and even incorrect specification of bias parameters still resulted in less bias compared to observed biased effects. Simultaneous multi-bias analysis is a useful method to investigate and understand how multiple biases can affect initial effect estimates, enhancing the validity and transparency of real-world evidence obtained from observational, longitudinal studies.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2023)

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Review Public, Environmental & Occupational Health

A systematic review of quantitative bias analysis applied to epidemiological research

Julie M. Petersen et al.

Summary: QBA applications in epidemiological research were rare but increasing over time. Most studies used QBA as secondary analyses to conventional methods or to assess the extent of bias. Common types of biases included misclassification, uncontrolled confounders, and selection bias. Many studies did not consider multiple biases or correlations between errors.

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2021)

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Article Public, Environmental & Occupational Health

Multiple-bias Sensitivity Analysis Using Bounds

Louisa H. Smith et al.

Summary: This study demonstrates a method to bound the total composite bias due to confounding, selection bias, and measurement error, and uses that bound to assess the sensitivity of a risk ratio to any combination of these biases. The approach is conservative and provides a simpler alternative to quantitative bias analysis.

EPIDEMIOLOGY (2021)

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Article Health Care Sciences & Services