The effect of nonindependence on significance testing in dyadic research

Abstract Relationship researchers regularly gather data from both members of the dyad, and these two scores are likely to be correlated. This nonindependence of observations can bias p values in significance testing if person is the unit in the statistical analysis. A method for determining how much bias results from dyadic interdependence is presented. Correction factors based on the degree of interdependence, design type, and the number of dyads are used to adjust the F statistic and its degrees of freedom to produce a corrected p value. Bias depends on the type of design and the degree of nonindependence, while the number of dyads in the study ordinarily has only a small effect on bias. Various strategies for controlling for nonindependence are briefly reviewed.