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Now showing items 41-47 of 47
Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data
(2023-05-16)
This article focuses on model-based clustering of subjects based on the shared relationships of subject-specific networks and covariates in scenarios when there are differences in the relationship between networks and ...
Developing and Testing Software for Linking Patient Data from Multiple Sources
(Patient-Centered Outcomes Research Institute (PCORI), 2022)
Background: Comparative effectiveness research (CER) and patient-centered outcomes research (PCOR) routinely use secondary data (eg, insurance claims, health records). Leveraging secondary data requires effective and ...
County-Level Projections of Medicaid Expansion's Impact in Texas
(Episcopal Health Foundation, 2020-09-14)
Texas is one of twelve states nationwide that has not expanded Medicaid, despite the largest number of uninsured residents in the country. One commonly cited reason is the budgetary implications of a large increase in ...
Sketching in High Dimensional Regression With Big Data Using Gaussian Scale Mixture Priors
(2023-05-16)
Bayesian computation of high dimensional linear regression models with popular Gaussian
scale mixture prior distributions using Markov Chain Monte Carlo (MCMC) or its variants
can be extremely slow or completely prohibitive ...
Review of Federal Access Policies for National Syndromic Surveillance Program Data: Findings and Implementation Strategies
(Council of State and Territorial Epidemiologists, 2023-02-23)
The current National Syndromic Surveillance Program (NSSP) data use agreements (DUAs) prohibit CDC from conducting surveillance at the state or local level. Instead, default access for CDC NSSP staff is limited to HHS ...
Multi-object Data Integration in the Study of Primary Progressive Aphasia
(2023-03-02)
This article focuses on a multi-modal imaging data application where structural/anatomical information from grey matter (GM) and brain connectivity information in the form of a brain connectome network from functional ...
A Covariance Based Clustering for Tensor Objects
(2023-03-03)
Clustering of tensors with limited sample size has become prevalent in a variety of application areas. Existing Bayesian model based clustering of tensors yields less accurate clusters when the tensor dimensions are ...