concrete: Targeted Estimation of Survival and Competing Risks in Continuous Time Article Swipe
David Chen
,
Helene C. W. Rytgaard
,
Edwin Fong
,
Jens M. Tarp
,
Maya Petersen
,
Mark J. van der Laan
,
Thomas Alexander Gerds
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2310.19197
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2310.19197
This article introduces the R package concrete, which implements a recently developed targeted maximum likelihood estimator (TMLE) for the cause-specific absolute risks of time-to-event outcomes measured in continuous time. Cross-validated Super Learner machine learning ensembles are used to estimate propensity scores and conditional cause-specific hazards, which are then targeted to produce robust and efficient plug-in estimates of the effects of static or dynamic interventions on a binary treatment given at baseline quantified as risk differences or risk ratios. Influence curve-based asymptotic inference is provided for TMLE estimates and simultaneous confidence bands can be computed for target estimands spanning multiple multiple times or events. In this paper we review the one-step continuous-time TMLE methodology as it is situated in an overarching causal inference workflow, describe its implementation, and demonstrate the use of the package on the PBC dataset.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2310.19197
- https://arxiv.org/pdf/2310.19197
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388093247
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388093247Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2310.19197Digital Object Identifier
- Title
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concrete: Targeted Estimation of Survival and Competing Risks in Continuous TimeWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-10-29Full publication date if available
- Authors
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David Chen, Helene C. W. Rytgaard, Edwin Fong, Jens M. Tarp, Maya Petersen, Mark J. van der Laan, Thomas Alexander GerdsList of authors in order
- Landing page
-
https://arxiv.org/abs/2310.19197Publisher landing page
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https://arxiv.org/pdf/2310.19197Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2310.19197Direct OA link when available
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Estimator, Inference, Causal inference, Computer science, Workflow, R package, Confidence interval, Econometrics, Statistics, Machine learning, Artificial intelligence, Mathematics, Database, Computational scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.interventions | 63 |
| abstract_inverted_index.time-to-event | 23 |
| abstract_inverted_index.cause-specific | 19, 43 |
| abstract_inverted_index.Cross-validated | 29 |
| abstract_inverted_index.continuous-time | 110 |
| abstract_inverted_index.implementation, | 125 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile |