Matching of subjects in research design could be a failure except in situation :
Matching variable having substantial correlation with the DV
Matching is a control technique in which participants are paired (or grouped) on some variable before being assigned to conditions, so that the groups are equivalent on that variable and it cannot explain differences in the dependent variable (DV).
Matching only gains anything when the matching variable is substantially correlated with the DV. Then it removes a real source of error variance, reduces within-group variability and increases the sensitivity (power) of the design. If the matching variable is unrelated to the DV, the groups are equated on something irrelevant: nothing is controlled, degrees of freedom are lost and subjects are wasted, so matching fails.
Matching followed by random assignment is good practice but it still does not help if the matched variable has no bearing on the DV. Balancing males and females across conditions is merely one instance of matching on sex, useful only if sex relates to the DV. A repeated measures design is a different strategy, where each participant serves as his or her own control.
Hence, the answer is Matching variable having substantial correlation with the DV.
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