False Positives Using Social Cognitive Mapping to Identify Children’s Peer Groups

• In Event: Innovations in Social Network Methods for Examining the Role of Peer Processes in Youth Development

Abstract

Decades of research demonstrate the importance of peers for child and adolescent development and psychological well-being (Bukowski, Laursen, & Rubin, 2018; Gifford-Smith & Brownell, 2003). Children and adolescents interact in peer groups with structural and behavioral features that are associated with a wide range of psychological, social, and academic outcomes (Birkett & Espelage, 2015; Espelage, Holt, & Henkel, 2003; Ryan, 2001). However, identifying peer groups can be challenging and represents a critical measurement task for developmental and clinical researchers (Kindermann & Gest, 2018). To overcome these challenges, Cairns and colleagues proposed social cognitive mapping (SCM), a method of peer group identification that involves identifying peer groups using multiple peer reports of groups of children that interact together in a setting such as a classroom (Cairns & Cairns, 1994; Cairns, Cairns, Neckerman, Gest, & Gariépy, 1988).

SCM has become a dominant method for identifying children’s peer groups from peer report data. The data are easy to collect, the ability to triangulate from peers reduces the impact of non-response, the analysis is easy to perform, and there is some evidence for its validity (Gest, Farmer, Cairns,& Xie, 2003). However, nothing is known about the extent to which SCM can yield false positives, where the method identifies peer groups from data that contain no or only weak evidence of their existence. In this presentation, we show that SCM has a high rate of false positives, assigning on average two-thirds of children to peer groups even when it is applied to random peer report data. We conclude that researchers should not use SCM, particularly as it is implemented in the SCM 4.0 program, to identify peer groups, and should explore alternative methods for identifying peer networks and peer groups from peer report data (Z. Neal, 2014).

Our presentation will begin by briefly reviewing SCM, providing an overview of its origins, where and how it has been used, how it works, and evidence for its accuracy. We then report on a series of four related studies. In study 1, we use empirical peer report data collected in a classroom that was also directly observed to demonstrate that SCM can detect true positives, identifying peer groups that are known (by observation) to exist. In study 2, we use simulated data that is identical to this empirical data except that it is random to demonstrate that SCM identifies peer groups even in data that contain no evidence of peer groups (i.e. false positives). In study 3, we extend study 2 by repeating the demonstration of SCM’s false positives in simulated peer report data from classrooms of varying size, child salience, and group salience. In study 4, we describe backbone extraction and community detection (BE-CD) as an alternative to SCM, repeating studies 1–3 using these techniques to demonstrate that they yield true positives and do not yield false positives. We conclude by drawing on these studies’ findings to offer recommendations for researchers seeking to identify children’s’ peer groups.

Authors

• Zachary P. Neal, Michigan State University
  Presenting Author

• Jennifer Watling Neal, Michigan State University
  Non-Presenting Author

• Rachel Domagalski, Michigan State University
  Non-Presenting Author