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Cognitive Social Structure (CSS) network studies collect relational data onrespondents' direct ties and their perception of ties among all otherindividuals in the network. When reporting their perception networks,respondents commit two types of errors, namely, omission (false negatives) andcommission (false positives) errors. We first assess the relationship betweenthese two error types, and their contributions on the overall respondentaccuracy. Next we propose a method for estimating networks based on perceptionsof a random sample of respondents from a bounded social network, which utilizesthe Receiving Operator Characteristic (ROC) curve for balancing the tradeoffsbetween omission and commission errors. A comparative numerical study showsthat the proposed estimation method performs well. This new method can beeasily integrated to organization studies that use randomized surveys to studymultiple organizations. The burgeoning field of multilevel analysis ofinter-organizational networks can also immensely benefit from this approach.

Omission and Commission Errors in Network Cognition and Network Estimation using ROC Curve