In epidemiology, collider stratification bias, the bias resulting from conditioning on a common effect of two causes, is oftentimes considered a type of selection bias, regardless of the conditioning methods employed. In this commentary, we distinguish between two types of collider stratification bias: collider restriction bias due to restricting to one level of a collider (or a descendant of a collider), and collider adjustment bias through inclusion of a collider (or a descendant of a collider) in a regression model. We argue that categorizing collider adjustment bias as a form of selection bias may lead to semantic confusion, as adjustment for a collider in a regression model does not involve selecting a sample for analysis. Instead, we propose that collider adjustment bias can be better viewed as a type of overadjustment bias. We further provide two distinct causal diagram structures to distinguish collider restriction bias and collider adjustment bias. We hope that such a terminological distinction can facilitate easier and clearer communication.

中文翻译：

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选择偏差需要选择：对撞机分层偏差的情况

在流行病学中，对撞机分层偏差（由对两个原因的共同影响进行调节而产生的偏差）通常被认为是一种选择偏差，无论采用何种调节方法。在本评论中，我们区分了两种类型的对撞机分层偏差：由于限制对撞机（或对撞机的后代）的一个级别而导致的对撞机限制偏差，以及通过包含对撞机（或对撞机的后代）而导致的对撞机调整偏差对撞机）在回归模型中。我们认为，将碰撞器调整偏差分类为选择偏差的一种形式可能会导致语义混乱，因为回归模型中碰撞器的调整不涉及选择样本进行分析。相反，我们建议对撞机调整偏差可以更好地视为一种过度调整偏差。我们进一步提供了两种不同的因果图结构来区分对撞机限制偏差和对撞机调整偏差。我们希望这样的术语区分能够促进更轻松、更清晰的沟通。