Search Results - "Li, Kendrick"
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Current Challenges With the Use of Test-Negative Designs for Modeling COVID-19 Vaccination and Outcomes
Published in American journal of epidemiology (24-02-2023)“…Abstract The widespread testing for severe acute respiratory syndrome coronavirus 2 infection has facilitated the use of test-negative designs (TNDs) for…”
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Journal Article -
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Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness
Published in Journal of the American Statistical Association (10-07-2023)“…The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness against the risk of acquiring infectious diseases in real-world…”
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3
Improved inference for fixed‐effects meta‐analysis of 2 × 2 tables
Published in Research synthesis methods (01-05-2020)“…Meta‐analysis of 2 × 2 tables is common and useful in research topics including analysis of adverse events and survey research data. Fixed‐effects inference…”
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A Bayesian “Sandwich” for Variance Estimation
Published in Statistical science (01-11-2024)Get full text
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5
Feature selection framework for functional connectome fingerprinting
Published in Human brain mapping (15-08-2021)“…The ability to uniquely characterize individual subjects based on their functional connectome (FC) is a key requirement for progress toward precision…”
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6
Regression-Based Proximal Causal Inference
Published in American journal of epidemiology (25-09-2024)“…Negative controls are increasingly used to evaluate the presence of potential unmeasured confounding in observational studies. Beyond the use of negative…”
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Group Convex Orthogonal Non-negative Matrix Tri-Factorization with Applications in FC Fingerprinting
Published 01-01-2020“…Functional magnetic resonance imaging (fMRI) data has been collected and studied in the neuroscience community for more than two decades. Methods have been…”
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Dissertation -
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Methods for Agnostic Statistical Inference
Published 01-01-2021“…A traditional goal of parametric statistics is to estimate some or all of a data-generating model's finite set of parameters, thereby turning data into…”
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Dissertation -
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Abstract 6382: Risk prediction of dyslipidemia in long-term survivors of childhood cancer: A report from the St. Jude Lifetime Cohort
Published in Cancer research (Chicago, Ill.) (22-03-2024)“…Abstract Background: Dyslipidemia is a significant contributor to the increased risk of cardiovascular morbidity and premature mortality in long-term survivors…”
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10
A Bayesian 'sandwich' for variance estimation
Published 30-06-2022“…Large-sample Bayesian analogs exist for many frequentist methods, but are less well-known for the widely-used 'sandwich' or 'robust' variance estimates. We…”
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11
Regression-Based Proximal Causal Inference
Published 31-01-2024“…Negative controls are increasingly used to evaluate the presence of potential unmeasured confounding in observational studies. Beyond the use of negative…”
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12
Regression-based proximal causal inference for right-censored time-to-event data
Published 13-09-2024“…Unmeasured confounding is one of the major concerns in causal inference from observational data. Proximal causal inference (PCI) is an emerging methodological…”
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Doubly Robust Proximal Causal Inference under Confounded Outcome-Dependent Sampling
Published 02-08-2022“…Unmeasured confounding and selection bias are often of concern in observational studies and may invalidate a causal analysis if not appropriately accounted…”
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Journal Article -
14
Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness
Published 23-03-2022“…The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness against the risk of acquiring infectious diseases in real-world…”
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Journal Article -
15
Test-negative designs with various reasons for testing: statistical bias and solution
Published 06-12-2023“…Test-negative designs are widely used for post-market evaluation of vaccine effectiveness, particularly in cases where randomization is not feasible. Differing…”
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16
Theory for identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework
Published 31-08-2021“…Synthetic control (SC) methods are commonly used to estimate the treatment effect on a single treated unit in panel data settings. An SC is a weighted average…”
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Journal Article