ArticleJournal of the American Statistical Association2017
Efficient Semiparametric Inference Under Two-Phase Sampling, With Applications to Genetic Association Studies.
Article in Journal of the American Statistical Association, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Optimal Two-Phase Sampling Designs for Generalized Raking Estimators With Multiple Parameters of Interest.Statistics in medicine · 2026Article
- Assessing surrogate heterogeneity in real world data using meta-learners.Journal of causal inference · 2026Article
- Valid and efficient inference for nonparametric variable importance in two-phase studies.Biometrics · 2025Article
- Ascertainment Conditional Maximum Likelihood for Continuous Outcome Under Two-Phase Response-Selective Design.Statistics in medicine · 2025Article
- sleev: An R Package for Semiparametric Likelihood Estimation with Errors in Variables.Journal of open source software · 2025Article
- A SEMIPARAMETRIC METHOD FOR RISK PREDICTION USING INTEGRATED ELECTRONIC HEALTH RECORD DATA.The annals of applied statistics · 2024Article
- Study design features increase replicability in cross-sectional and longitudinal brain-wide association studies.bioRxiv : the preprint server for biology · 2024Article
- Article
- Two-phase stratified sampling and analysis for predicting binary outcomes.Biostatistics (Oxford, England) · 2023Article
- Goodness-of-fit two-phase sampling designs for time-to-event outcomes: a simulation study based on New York University Women's Health Study for breast cancer.BMC medical research methodology · 2023Article
- Model misspecification and robust analysis for outcome-dependent sampling designs under generalized linear models.Statistics in medicine · 2023Article
- Generalized case-control sampling under generalized linear models.Biometrics · 2023Article
- Efficient odds ratio estimation under two-phase sampling using error-prone data from a multi-national HIV research cohort.Biometrics · 2022Article
- Optimal sampling for design-based estimators of regression models.Statistics in medicine · 2022Article
- Two-Phase Sampling Designs for Data Validation in Settings with Covariate Measurement Error and Continuous Outcome.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2021Article
- Two-wave two-phase outcome-dependent sampling designs, with applications to longitudinal binary data.Statistics in medicine · 2021Article
- A novel age-informed approach for genetic association analysis in Alzheimer's disease.Alzheimer's research & therapy · 2021Article
- Efficient semiparametric inference for two-phase studies with outcome and covariate measurement errors.Statistics in medicine · 2021Article
- Optimal multiwave sampling for regression modeling in two-phase designs.Statistics in medicine · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
In modern epidemiological and clinical studies, the covariates of interest may involve genome sequencing, biomarker assay, or medical imaging and thus are prohibitively expensive to measure on a large number of subjects. A cost-effective solution is the two-phase design, under which the outcome and inexpensive covariates are observed for all subjects during the first phase and that information is used to select subjects for measurements of expensive covariates during the second phase. For example, subjects with extreme values of quantitative traits were selected for whole-exome sequencing in the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP). Herein, we consider general two-phase designs, where the outcome can be continuous or discrete, and inexpensive covariates can be continuous and correlated with expensive covariates. We propose a semiparametric approach to regression analysis by approximating the conditional density functions of expensive covariates given inexpensive covariates with B-spline sieves. We devise a computationally efficient and numerically stable EM-algorithm to maximize the sieve likelihood. In addition, we establish the consistency, asymptotic normality, and asymptotic efficiency of the estimators. Furthermore, we demonstrate the superiority of the proposed methods over existing ones through extensive simulation studies. Finally, we present applications to the aforementioned NHLBI ESP.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.