False positives using social cognitive mapping to identify childrens' peer groups

TL;DR

This paper critically evaluates social cognitive mapping (SCM) for identifying children's peer groups, revealing high false positive rates and proposing alternative methods like backbone extraction and community detection.

Contribution

It demonstrates the high false positive risk of SCM and introduces alternative network analysis techniques for more accurate peer group identification.

Findings

SCM produces many false positives even with random data

Backbone extraction and community detection reduce false positives

Recommendations provided for researchers on peer group identification

Abstract

Children and adolescents interact in peer groups, which are known to influence a range of psychological and behavioral outcomes. In developmental psychology and related disciplines, social cognitive mapping (SCM), as implemented with the SCM 4.0 software, is the most commonly used method for identifying peer groups from peer report data. However, in a series of four studies, we demonstrate that SCM has an unacceptably high risk of false positives. Specifically, we show that SCM will identify peer groups even when applied to random data. We introduce backbone extraction and community detection as one promising alternative to SCM, and offer several recommendations for researchers seeking to identify peer groups from peer report data.