Resultado de búsqueda
Collider bias is a distortion of an exposure-outcome association caused by controlling for a common effect of both. Learn how to identify and prevent collider bias with causal diagrams and examples from Sackett and obesity paradox.
What Is Collider Bias? Collider bias occurs when an exposure and outcome (or factors causing these) each influence a common third variable and that variable or collider is controlled for by design or analysis. 3 In contrast, confounding occurs when an exposure and outcome have a shared common cause that is not controlled for.
18 de feb. de 2022 · So-called confounders are well known, but distortion by collider bias (CB) has received little attention in medical research to date. The goal of this article is to present the principle of CB, and measures that can be taken to avoid it, by way of a few illustrative examples.
Berkson's paradox, also known as Berkson's bias, collider bias, or Berkson's fallacy, is a result in conditional probability and statistics which is often found to be counterintuitive, and hence a veridical paradox. It is a complicating factor arising in statistical tests of proportions.
12 de nov. de 2020 · In this paper, we discuss why collider bias should be of particular concern to observational studies of COVID-19 infection and disease risk, and show how sample selection can lead to dramatic...
23 de feb. de 2023 · Collider bias is a bias induced by conditioning on disease incidence in studies of disease progression, such as survival or prognosis. This article reviews methods to detect and adjust for collider bias in genetic and Mendelian randomisation studies using individual- and summary-level data.
This JAMA Guide to Statistics and Methods describes collider bias, illustrates examples in directed acyclic graphs, and explains how it can threaten the internal validity of a study and the accurate estimation of causal relationships in randomized clinical trials and observational studies.
