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48 papers · 1 filter
Optimizing Complex Health Intervention Packages through the Learn-As-you-GO (LAGO) Design
Donna Spiegelman, Dong Roman Xu, Ante Bing +11
In the face of vast numbers of preventable deaths worldwide and gaping disparities in their distribution, we cannot afford to conduct null and inconclusive effectiveness and implem…
Improving Transportability of Regression Calibration Under the Main/External Validation Study Design
Zexiang Li, Donna Spiegelman, Molin Wang +2
In epidemiology, obtaining accurate individual exposure measurements can be costly and challenging. Thus, these measurements are often subject to error. Regression calibration with…
Thinning a Wishart Random Matrix
Ameer Dharamshi, Anna Neufeld, Lucy L. Gao +2
Recent work has explored data thinning, a generalization of sample splitting that involves decomposing a (possibly matrix-valued) random variable into independent components. In th…
A tutorial on conducting sample size and power calculations for detecting treatment effect heterogeneity in cluster randomized trials with linear mixed models
Mary Ryan Baumann, Monica Taljaard, Patrick J. Heagerty +4
Cluster-randomized trials (CRTs) are a well-established class of designs for evaluating community-based interventions. An essential task in planning these trials is determining the…
The causal effects of modified treatment policies under network interference
Salvador V. Balkus, Scott W. Delaney, Nima S. Hejazi
Modified treatment policies are a widely applicable class of interventions useful for studying the causal effects of continuous exposures. Approaches to evaluating their causal eff…
Scalable Gaussian Process Regression Via Median Posterior Inference for Estimating Multi-Pollutant Mixture Health Effects
Aaron Sonabend, Jiangshan Zhang, Edgar Castro +3
Humans are exposed to complex mixtures of environmental pollutants rather than single chemicals, necessitating methods to quantify the health effects of such mixtures. Research on…