ArticleJournal of the American Statistical Association2016
Constrained Maximum Likelihood Estimation for Model Calibration Using Summary-level Information from External Big Data Sources.
Article in Journal of the American Statistical Association, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 1 of them a synthesis that pooled it.
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Who cites it
60 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-inference framework to integrate multiple external models into a current study.Biostatistics (Oxford, England) · 2023Pooled it
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- TLS-Tractor: A transfer learning framework for incorporating summary-statistics into local ancestry-aware GWAS in admixed populations.medRxiv : the preprint server for health sciences · 2026Article
- Improved risk prediction via cross-domain calibration in a retrospective case-control study.The Canadian journal of statistics = Revue canadienne de statistique · 2026Article
- A new information integration framework for complex models with applications to real-world data.Statistical methods in medical research · 2026Article
- Towards a Unified Theory for Semiparametric Data Fusion with Individual-Level Data.Annals of statistics · 2026Article
- Mediation with External Summary Statistic Information.Biostatistics (Oxford, England) · 2025Article
- Selection processes, transportability, and failure time analysis in life history studies.Biostatistics (Oxford, England) · 2025Article
- A Review of Methods for Research Synthesis.Statistics in medicine · 2025Article
- The Effect of Alcohol Intake on Brain White Matter Microstructural Integrity: A New Causal Inference Framework for Incomplete Phenomic Data.Journal of the American Statistical Association · 2025Article
- Robust angle-based transfer learning in high dimensions.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2025Article
- KULLBACK-LEIBLER-BASED DISCRETE FAILURE TIME MODELS FOR INTEGRATION OF PUBLISHED PREDICTION MODELS WITH NEW TIME-TO-EVENT DATASET.The annals of applied statistics · 2025Article
- Expanding scope of genetic studies in the era of biobanks.Human molecular genetics · 2025Article
- Improving estimation efficiency for survival data analysis by integrating a coarsened time-to-event outcome from an external study.Biometrics · 2025Article
- A comparison of some existing and novel methods for integrating historical models to improve estimation of coefficients in logistic regression.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2025Article
- A Weighted Survival Regression Framework for Incorporating External Prediction Information.Journal of statistical theory and practice · 2025Article
- Article
- EFFICIENT AND MULTIPLY ROBUST RISK ESTIMATION UNDER GENERAL FORMS OF DATASET SHIFT.Annals of statistics · 2024Article
- Improving prediction of linear regression models by integrating external information from heterogeneous populations: James-Stein estimators.Biometrics · 2024Article
- Integrating external summary information in the presence of prior probability shift: an application to assessing essential hypertension.Biometrics · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Information from various public and private data sources of extremely large sample sizes are now increasingly available for research purposes. Statistical methods are needed for utilizing information from such big data sources while analyzing data from individual studies that may collect more detailed information required for addressing specific hypotheses of interest. In this article, we consider the problem of building regression models based on individual-level data from an "internal" study while utilizing summary-level information, such as information on parameters for reduced models, from an "external" big data source. We identify a set of very general constraints that link internal and external models. These constraints are used to develop a framework for semiparametric maximum likelihood inference that allows the distribution of covariates to be estimated using either the internal sample or an external reference sample. We develop extensions for handling complex stratified sampling designs, such as case-control sampling, for the internal study. Asymptotic theory and variance estimators are developed for each case. We use simulation studies and a real data application to assess the performance of the proposed methods in contrast to the generalized regression (GR) calibration methodology that is popular in the sample survey literature.
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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.