Scholarlink

<p>Composite risk instruments compress multiple indicators into a single severity score. This is operationally efficient, but it obscures how risk factors are organised and how equifinal pathways generate the same total score. We propose a network-based framework to examine configuration-level heterogeneity among score-equivalent cases. Using 17,272 administrative assessments from a criminological risk instrument, we analyse item co-occurrence within narrow, overlapping score windows to hold overall severity constant. Recurrent configurations are detected via clustering based on Jaccard similarity, their stability is evaluated across windows, and their internal structures are estimated using Ising network models. Identical scores map onto distinct and recurring network architectures, showing that relational structure contains substantively relevant information beyond additive scoring. More broadly, the framework illustrates how network psychometrics can uncover latent structural heterogeneity in applied measurement instruments and in other administrative score-based systems.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Same score, different network: configuration-level heterogeneity in composite risk measures

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月22日

查看全文
  • Jorge Fábrega,
  • Aníbal Olivera

摘要

Composite risk instruments compress multiple indicators into a single severity score. This is operationally efficient, but it obscures how risk factors are organised and how equifinal pathways generate the same total score. We propose a network-based framework to examine configuration-level heterogeneity among score-equivalent cases. Using 17,272 administrative assessments from a criminological risk instrument, we analyse item co-occurrence within narrow, overlapping score windows to hold overall severity constant. Recurrent configurations are detected via clustering based on Jaccard similarity, their stability is evaluated across windows, and their internal structures are estimated using Ising network models. Identical scores map onto distinct and recurring network architectures, showing that relational structure contains substantively relevant information beyond additive scoring. More broadly, the framework illustrates how network psychometrics can uncover latent structural heterogeneity in applied measurement instruments and in other administrative score-based systems.