Survey instruments utilized to quantify relationships, or aspects of relationships, may introduce multiple sources of nonindependence"”clustered variance"”into scores, including from actor, alter and dyadic sources. Estimating the magnitude of actor, alter and dyad nonindependence and their impact on the reliability of scores is an important step towards assuring quality data. Multilevel confirmatory factor analysis and the social relations model offer methods for quantifying the influence and estimating the reliability of multiple sources of clustered variance. The use of these methods is illustrated in the analysis of data gathered via a survey designed to quantify relational embeddedness in social network analyses.