Null Controls for the Matthew Effect Index: A Primer

The Matthew Effect Index (MEI) is a new cohort-level effect-size index first developed in serious games analytics, measuring divergence between two cohorts produced by an information-gating mechanism. Like any new measurement instrument, MEI requires principled validation before its readings can be trusted. This primer demonstrates pipeline validation through a battery of five null controls, each constructed to address a specific skeptical objection: parametric noise (two variants), label permut