17 citations · 21 across the 16 of their papers we have counts for
6 papers · 1 filter
Temporal Models for Demographic and Global Health Outcomes in Multiple Populations: Introducing the Normal-with-Optional-Shrinkage Data Model Class
Leontine Alkema, Herbert Susmann, Evan Ray
Statistical models are used to produce estimates of demographic and global health indicators in populations with limited data. Such models integrate multiple data sources to produc…
Causal-DRF: Conditional Kernel Treatment Effect Estimation using Distributional Random Forest
Jeffrey Näf, Junhyung Park, Herbert Susmann
The conditional average treatment effect (CATE) is a commonly targeted statistical parameter for measuring the effect of a treatment conditional on covariates. However, the CATE wi…
Doubly Robust Nonparametric Efficient Estimation for Provider Evaluation
Herbert Susmann, Yiting Li, Mara A. McAdams-DeMarco +2
Provider profiling has the goal of identifying healthcare providers with exceptional patient outcomes. When evaluating providers, adjustment is necessary to control for differences…
Flexibly Modeling Shocks to Demographic and Health Indicators with Bayesian Shrinkage Priors
Herbert Susmann, Leontine Alkema
Demographic and health indicators may exhibit short or large short-term shocks; for example, armed conflicts, epidemics, or famines may cause shocks in period measures of life expe…
Bayesian Projection of Extant Refugee and Asylum Seeker Populations
Herbert Susmann, Adrian E. Raftery
Estimates of future migration patterns are of broad interest in demography. Forced migration, including refugee and asylum seekers, plays an important role in overall migration pat…
Longitudinal Generalizations of the Average Treatment Effect on the Treated for Multi-valued and Continuous Treatments
Herbert Susmann, Nicholas T. Williams, Kara E. Rudolph +1
The Average Treatment Effect on the Treated (ATT) is a common causal parameter defined as the average effect of a binary treatment among the subset of the population receiving trea…