4 citations · 4 across the 6 of their papers we have counts for
6 papers
Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples
Kangrui Liu, Lingxiao Wang, Yan Li
Nonprobability samples have rapidly emerged to address time-sensitive priority topics in a variety of fields. While these data are timely, they are prone to selection bias. To miti…
Using Model-Assisted Calibration Methods to Improve Efficiency of Regression Analyses with Two-Phase Samples under Complex Survey Designs
Lingxiao Wang
Two-phase sampling designs are frequently employed in epidemiological studies and large-scale health surveys. In such designs, certain variables are exclusively collected within a…
Data-integration with pseudoweights and survey-calibration: application to developing US-representative lung cancer risk models for use in screening
Lingxiao Wang, Yan Li, Barry Graubard +1
Accurate cancer risk estimation is crucial to clinical decision-making, such as identifying high-risk people for screening. However, most existing cancer risk models incorporate da…
Representative Pure Risk Estimation by Using Data from Epidemiologic Studies, Surveys, and Registries: Estimating Risks for Minority Subgroups
Lingxiao Wang, Yan Li, Barry I. Graubard +1
Representative risk estimation is fundamental to clinical decision-making. However, risks are often estimated from non-representative epidemiologic studies, which usually underrepr…
Efficient and Robust Propensity-Score-Based Methods for Population Inference using Epidemiologic Cohorts
Lingxiao Wang, Barry I. Graubard, Hormuzd A. Katki +1
Most epidemiologic cohorts are composed of volunteers who do not represent the general population. To enable population inference from cohorts, we and others have proposed utilizin…
Adjusted Logistic Propensity Weighting Methods for Population Inference using Nonprobability Volunteer-Based Epidemiologic Cohorts
Lingxiao Wang, Richard Valliant, Yan Li
Many epidemiologic studies forgo probability sampling and turn to nonprobability volunteer-based samples because of cost, response burden, and invasiveness of biological samples. H…