{"accessLevel": "public", "bureauCode": ["020:00"], "contactPoint": {"fn": "Michael Dumelle", "hasEmail": "mailto:dumelle.michael@epa.gov"}, "description": "These data contain several publicly-available data sets that are used to elucidate the methods in the paper, including data on seal counts in Alaska, county-aggregated demographic data, and heavy metal data in Alaska. \n\nThis dataset is associated with the following publication:\nVer Hoef, J., E. Blagg, M. Dumelle, P. Dixon, D. Zimmerman, and P. Conn. Marginal Inference for Hierarchical Generalized Linear Mixed Models with Patterned Covariance Matrices Using the Laplace Approximation.   ENVIRONMETRICS. John Wiley & Sons Incorporated, New York, NY, USA, 35(7): e2872, (2024).", "distribution": [{"accessURL": "https://github.com/USEPA/mhglmm.laplace", "title": "https://github.com/USEPA/mhglmm.laplace"}], "identifier": "https://doi.org/10.23719/1531697", "keyword": ["Correlation", "Generalized Linear Model", "Mixed Model", "Spatial Model", "Statistsics"], "license": "https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html", "modified": "2024-05-16", "programCode": ["020:000"], "publisher": {"name": "U.S. EPA Office of Research and Development (ORD)", "subOrganizationOf": {"name": "U.S. Environmental Protection Agency", "subOrganizationOf": {"name": "U.S. Government"}}}, "references": ["https://doi.org/10.1002/env.2872"], "rights": null, "title": "Data for \"Marginal Inference for Hierarchical Generalized Linear Mixed Models with Patterned Covariance Matrices Using the Laplace Approximation\""}