5 papers · 1 filter
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…