Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Susmann, Herbert P."'
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 produce estimates and forecasts with uncertainty based on model assumptions.
Externí odkaz:
http://arxiv.org/abs/2411.18646
Autor:
Näf, Jeffrey, Susmann, Herbert
The conditional average treatment effect (CATE) is a commonly targeted statistical parameter for measuring the mean effect of a treatment conditional on covariates. However, the CATE will fail to capture effects of treatments beyond differences in co
Externí odkaz:
http://arxiv.org/abs/2411.08778
Provider profiling has the goal of identifying healthcare providers with exceptional patient outcomes. When evaluating providers, adjustment is necessary to control for differences in case-mix between different providers. Direct and indirect standard
Externí odkaz:
http://arxiv.org/abs/2410.19073
Autor:
Susmann, Herbert, Alkema, Leontine
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 expectancy. Statistical models for estimating historical trends and genera
Externí odkaz:
http://arxiv.org/abs/2410.09217
Autor:
Susmann, Herbert, Raftery, Adrian E.
Estimates of future migration patterns are a crucial input to world population projections. Forced migration, including refugee and asylum seekers, plays an important role in overall migration patterns, but is notoriously difficult to forecast. We pr
Externí odkaz:
http://arxiv.org/abs/2405.06857
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 treatment. We propose a novel family of parameters, Generalized ATTs (GATT
Externí odkaz:
http://arxiv.org/abs/2405.06135
Conformal Inference (CI) is a popular approach for generating finite sample prediction intervals based on the output of any point prediction method when data are exchangeable. Adaptive Conformal Inference (ACI) algorithms extend CI to the case of seq
Externí odkaz:
http://arxiv.org/abs/2312.00448
Autor:
Susmann, Herbert, Chambaz, Antoine
Estimating quantiles of an outcome conditional on covariates is of fundamental interest in statistics with broad application in probabilistic prediction and forecasting. We propose an ensemble method for conditional quantile estimation, Quantile Supe
Externí odkaz:
http://arxiv.org/abs/2310.19343
Aggregate measures of family planning are used to monitor demand for and usage of contraceptive methods in populations globally, for example as part of the FP2030 initiative. Family planning measures for low- and middle-income countries are typically
Externí odkaz:
http://arxiv.org/abs/2302.00951
Autor:
Susmann, Herbert, Chambaz, Antoine
Two of the principle tasks of causal inference are to define and estimate the effect of a treatment on an outcome of interest. Formally, such treatment effects are defined as a possibly functional summary of the data generating distribution, and are
Externí odkaz:
http://arxiv.org/abs/2301.10630