{
  "abstract": "Process data from computer-based assessments record the sequence and timing of actions through which respondents solve a task, providing information about both the pace and structure of problem-solving behavior. Modeling such processes across countries is challenging because country-by-response-group cells are often small and unbalanced and the observed transition supports can differ substantially across countries. We propose a hierarchical framework that integrates a Bayesian multi-state survival model with a network-based representation of transition structure. Partial pooling across countries yields country-specific covariate and key-action effects, transition speed, and estimates of between-country heterogeneity. Posterior transition probability networks are embedded in a common latent space using a directed graph auto-encoder adapted to heterogeneous supports, and 1-Wasserstein distances between node-role distributions are evaluated across posterior draws to characterize global network structure while propagating estimation uncertainty. We apply the framework to two problem-solving items from the Programme for the International Assessment of Adult Competencies across 14 countries. The results reveal cross-country heterogeneity in transition speed, systematic response-group differences in global network organization, item-dependent variation in within-group dispersion across countries, and local differences in routing around shared intermediate actions.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.22735",
  "author_total": 4,
  "authors": [
    {
      "name": "Doungjun Kim"
    },
    {
      "name": "Daeun Hwangbo"
    },
    {
      "name": "Minjeong Jeon"
    },
    {
      "name": "Ick Hoon Jin"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/eetcy6jmj9sjv.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.22735",
  "fulltext_url": null,
  "id": "eetcy6jmj9sjv",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.22735",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.AP"
    ],
    [
      "openalex",
      "1803|Psychometric Methodologies and Testing"
    ]
  ],
  "openalex": "W7214025091",
  "pdf_url": "https://arxiv.org/pdf/2609.22735",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-19",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/eetcy6jmj9sjv.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:33Z",
      "native_id": "2609.22735",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.22735"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "Modeling Transition Dynamics and Network Structure in Cross-National Process Data: A Hierarchical Multi-State Survival Framework",
  "title_text": "Modeling Transition Dynamics and Network Structure in Cross-National Process Data: A Hierarchical Multi-State Survival Framework",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:33Z",
  "url": "https://research.draconitic.com/paper/eetcy6jmj9sjv",
  "venue": "arXiv",
  "versions": []
}