Doubly Robust Triple Cross-Fit Estimation for Causal Inference with Imaging Data Article Swipe
Da Ke
,
Xiaoxiao Zhou
,
Qinglong Yang
,
Xinyuan Song
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s12561-024-09458-1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s12561-024-09458-1
This paper develops a novel doubly robust triple cross-fit estimator to estimate the average treatment effect (ATE) using observational and imaging data. The construction of the proposed estimator consists of two stages. The first stage extracts representative image features using the high-dimensional functional principal component analysis model. The second stage incorporates the image features into the propensity score and outcome models and then analyzes these models through machine learning algorithms. A doubly robust estimator for ATE is obtained based on the estimation results. In addition, we extend the double cross-fit to a triple cross-fit algorithm to accommodate the imaging data that typically exhibit more subtle variation and yield less stable estimation compared to conventional scalar variables. The simulation study demonstrates the satisfactory performance of the proposed estimator. An application to the Alzheimer’s Disease Neuroimaging Initiative dataset confirms the utility of our method.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s12561-024-09458-1
- OA Status
- hybrid
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402942704
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https://openalex.org/W4402942704Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s12561-024-09458-1Digital Object Identifier
- Title
-
Doubly Robust Triple Cross-Fit Estimation for Causal Inference with Imaging DataWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-28Full publication date if available
- Authors
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Da Ke, Xiaoxiao Zhou, Qinglong Yang, Xinyuan SongList of authors in order
- Landing page
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https://doi.org/10.1007/s12561-024-09458-1Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://doi.org/10.1007/s12561-024-09458-1Direct OA link when available
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Causal inference, Biostatistics, Inference, Estimation, Computer science, Econometrics, Data mining, Statistics, Artificial intelligence, Mathematics, Economics, Medicine, Public health, Management, NursingTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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25Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.demonstrates | 120 |
| abstract_inverted_index.incorporates | 51 |
| abstract_inverted_index.satisfactory | 122 |
| abstract_inverted_index.Alzheimer’s | 132 |
| abstract_inverted_index.observational | 19 |
| abstract_inverted_index.representative | 37 |
| abstract_inverted_index.high-dimensional | 42 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.20726195 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |