activity
20212024
collaborators

8 papers

cs.CL2024

From Narratives to Numbers: Valid Inference Using Language Model Predictions from Verbal Autopsy Narratives

Shuxian Fan, Adam Visokay, Kentaro Hoffman +4

In settings where most deaths occur outside the healthcare system, verbal autopsies (VAs) are a common tool to monitor trends in causes of death (COD). VAs are interviews with a su…

stat.AP2024

Bayesian analysis of verbal autopsy data using factor models with age- and sex-dependent associations between symptoms

Tsuyoshi Kunihama, Zehang Richard Li, Samuel J. Clark +1

Verbal autopsies (VAs) are extensively used to investigate the population-level distributions of deaths by cause in low-resource settings without well-organized vital statistics sy…

stat.ME2024

Dempster-Shafer P-values: Thoughts on an Alternative Approach for Multinomial Inference

Kentaro Hoffman, Kai Zhang, Tyler McCormick +1

In this paper, we demonstrate that a new measure of evidence we developed called the Dempster-Shafer p-value which allow for insights and interpretations which retain most of the s…

stat.ME2024

Do We Really Even Need Data?

Kentaro Hoffman, Stephen Salerno, Awan Afiaz +2

As artificial intelligence and machine learning tools become more accessible, and scientists face new obstacles to data collection (e.g. rising costs, declining survey response rat…

stat.AP2023

Respondent-Driven Sampling: An Overview in the Context of Human Trafficking

Jessica P. Kunke, Adam Visokay, Tyler H. McCormick

Respondent-driven sampling (RDS) is both a sampling strategy and an estimation method. It is commonly used to study individuals that are difficult to access with standard sampling…

stat.AP2023

Bayesian Age Category Reconciliation for Age- and Cause-specific Under-five Mortality Estimates

Shuxian Fan, Li Liu, Jamie Perin +1

Age-disaggregated health data is crucial for effective public health planning and monitoring. Monitoring under-five mortality, for example, requires highly detailed age data since…