@uebernerd
It's clearly statistics with p-value:
1:1 => p=0.3173105188
2:1 => p=0.0455001240
3:1 => p=0.0026999344
4:1 => p=0.0000633721
5:1 => p=0.0000005742

But the problem is elsewhere. In experimental social science "effect size" and "sampling error" are artifacts of method, when data rarely meet the assumptions.

Triangulation is IMHO better idea than efforts to lower p-values: https://www.nature.com/articles/d41586-018-01023-3