Match tier
Likely match
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-10-01
A
Allen Smith
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
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1 pubs
Research Areas
Biography and Research Information
OverviewAI-generated summary
Allen Smith's research focuses on statistical methods for time-to-event prediction. His work includes a methodological comparison of different approaches for predicting diagnosed cannabis use disorder among medical cannabis cardholders in Arkansas. This study, published in 2026, utilized retrospective data to evaluate predictive modeling techniques.
Metrics
- Publications: 1
Selected Publications
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A Methodological Comparison of Three Landmarking Approaches for Time-to-Event Prediction: Predicting Diagnosed Cannabis Use Disorder Among Medical Cannabis Cardholders in Arkansas (2026)
Collaboration Network
Top Collaborators
Horacio Gómez-Acevedo
University of Arkansas for Medical Sciences
1 shared publication
In database
- A Methodological Comparison of Three Landmarking Approaches for Time-to-Event Prediction: Predicting Diagnosed Cannabis Use Disorder Among Medical Cannabis Cardholders in Arkansas
Corey Hayes
University of Arkansas for Medical Sciences
1 shared publication
In database
- A Methodological Comparison of Three Landmarking Approaches for Time-to-Event Prediction: Predicting Diagnosed Cannabis Use Disorder Among Medical Cannabis Cardholders in Arkansas
Melody Greer
University of Arkansas for Medical Sciences
1 shared publication
In database
- A Methodological Comparison of Three Landmarking Approaches for Time-to-Event Prediction: Predicting Diagnosed Cannabis Use Disorder Among Medical Cannabis Cardholders in Arkansas
Chenghui Li
University of Arkansas for Medical Sciences
1 shared publication
In database
- A Methodological Comparison of Three Landmarking Approaches for Time-to-Event Prediction: Predicting Diagnosed Cannabis Use Disorder Among Medical Cannabis Cardholders in Arkansas
Bradley C. Martin
University of Arkansas for Medical Sciences
1 shared publication
In database
- A Methodological Comparison of Three Landmarking Approaches for Time-to-Event Prediction: Predicting Diagnosed Cannabis Use Disorder Among Medical Cannabis Cardholders in Arkansas
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