{
  "abstract": "Longitudinal treatments are common in social science research but are often reduced to ever-versus-never exposure indicators that obscure their time-varying nature. This study shows how causal questions can be clarified by defining treatments through explicit intervention regimes rather than collapsed summaries. We introduce this framework by linking the longitudinal setting to single-time-point causal inference and extending it to time-varying exposures, sequential identification assumptions, and estimation using targeted maximum likelihood estimation (TMLE). We also address practical challenges, including missing data and positivity violations. Using data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999 (ECLS-K), we examine the effect of special education participation on 5th-grade mathematics achievement. Comparing static and dynamic regimes, we find meaningful differences: always-treated versus never-treated contrasts yield the largest negative estimates, while rule-based dynamic regimes produce substantially smaller effects. These results highlight the importance of well-defined interventions for interpreting longitudinal treatment effects.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "name": "Bryan Keller"
    },
    {
      "name": "Lindsey Liu"
    },
    {
      "name": "Yingqi Huan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9b7c5ydetx1e0.bib",
  "cited_by": 0,
  "doi": "10.31234/osf.io/fs7tw_v2",
  "fulltext_url": null,
  "id": "9b7c5ydetx1e0",
  "issns": [],
  "landing_url": "https://osf.io/preprints/psyarxiv/fs7tw_v2/",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Educational Psychology"
    ],
    [
      "bepress",
      "Experimental Design and Sample Surveys"
    ],
    [
      "bepress",
      "Learner"
    ],
    [
      "bepress",
      "Quantitative Methods"
    ],
    [
      "bepress",
      "Quantitative Psychology"
    ],
    [
      "bepress",
      "Social and Behavioral Sciences"
    ],
    [
      "bepress",
      "Statistical Methods"
    ],
    [
      "openalex",
      "2613|Advanced Causal Inference Techniques"
    ]
  ],
  "openalex": "W7213511934",
  "pdf_url": "https://osf.io/fs7tw/download",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-17",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9b7c5ydetx1e0.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:24:33Z",
      "native_id": "fs7tw",
      "source": "osf",
      "url": "https://osf.io/preprints/psyarxiv/fs7tw_v2/"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "bepress:Statistical Methods",
      "subfield": "statistics"
    }
  ],
  "title": "Estimating Effects of Time-Varying Special Education Regimes Using Targeted Maximum Likelihood",
  "title_text": "Estimating Effects of Time-Varying Special Education Regimes Using Targeted Maximum Likelihood",
  "type": "preprint",
  "updated_at": "2026-10-30T12:24:33Z",
  "url": "https://research.draconitic.com/paper/9b7c5ydetx1e0",
  "venue": "PsyArXiv",
  "versions": []
}