I think your example is closer to a survivor bias, while the article describes more of a collider bias. Survivor bias arises when you study what you think is a

I think your example is closer to a survivor bias, while the article describes more of a collider bias. Survivor bias arises when you study what you think is a full population, while in fact you're looking at a selected sample that did survive the very thing you're studying. A classical example in finance happens when you want to study, say, the performance of tech companies over the last 10 years. If you just pick current tech companies and look at their past performance, you will be biased towards companies that did make it. You have to include companies that don't exist anymore but would have been included were you to perform the study say 5 years ago.