Step 1: Understanding concomitant variation.
- It refers to the extent to which changes in one variable are associated with changes in another variable.
- Strong, consistent patterns across multiple studies increase confidence in causality.
Step 2: Why others are wrong.
- (a) Time order is important but is a separate criterion.
- (b) Role of evidence is too vague.
- (d) Elimination of other factors is another separate condition, not this one.
\[
\boxed{(c)}
\]