3 citations · 4 across the 4 of their papers we have counts for
4 papers
Exploring the big data paradox for various estimands using vaccination data from the global COVID-19 Trends and Impact Survey (CTIS)
Youqi Yang, Walter Dempsey, Peisong Han +4
Selection bias poses a challenge to statistical inference validity in non-probability surveys. This study compared estimates of the first-dose COVID-19 vaccination rates among Indi…
Improving Estimation Efficiency for Two-Phase, Outcome-Dependent Sampling Studies
Menglu Che, Peisong Han, Jerald F. Lawless
Two-phase outcome dependent sampling (ODS) is widely used in many fields, especially when certain covariates are expensive and/or difficult to measure. For two-phase ODS, the condi…
Robust Causal Inference of Drug-drug Interactions
Di Shu, Peisong Han, Sean Hennessy +1
There is growing interest in developing causal inference methods for multi-valued treatments with a focus on pairwise average treatment effects. Here we focus on a clinically impor…
Variable selection with multiply-imputed datasets: choosing between stacked and grouped methods
Jiacong Du, Jonathan Boss, Peisong Han +5
Penalized regression methods, such as lasso and elastic net, are used in many biomedical applications when simultaneous regression coefficient estimation and variable selection is…