I'm a rookie with statistics, and I'm struggling to understand this:
- it is well known that a confounding factor can cause a spurious association, leading to rejecting a true null hypothesis (i.e. due to the confounding factor Z, I could conclude that there is a causal relationship between X and Y, while one is not there)
- the question is: can the opposite also be true? I.e. can a confounding factor lead to failing to reject a false null hypothesis? (i.e. somehow 'masking' a possibly existent causal association.) If yes, what would be a convincing example?