Survivorship bias

What it is

Drawing conclusions from the winners who remain visible while overlooking the many that dropped out, so success looks easier or likelier than it is.

Example Studying successful founders who dropped out of college and concluding that dropping out helps.

Cherry picking fallacy
Survivorship bias is cherry picking done by the world: only the survivors are visible, so only they get studied.
Self-selection bias bias
Both distort samples before analysis even starts: survivors and volunteers are not representative.
Alternative paths bias
We only see the path that survived, not the many that didn't.
Argument from silence fallacy
What is missing from the record (silence) is often missing because of how the record was selected, as in survivorship bias.
Beginner's luck bias
Early successes in risky fields are the ones that stay visible, which makes luck look like skill.
Feature-positive effect bias
We notice the cases that are present and miss those that are absent, such as the dropouts and failures.
Swimmer's body illusion bias
Both confuse who is in the group with what the group does to them.
Intention-to-treat error bias
Analysing only those who completed a programme ignores the dropouts, which is survivorship bias in studies.