PPT-Cross-jurisdictional data linkage of Commonwealth data

The experience of the VALiD project Katherine Duszynski Discipline of Paediatrics UNIVERSITY OF ADELAIDE Acknowledgements Funding support This research was supported under Australian Research Councils . Bruce Armstrong AM FAA. Adjunct Professor, University of WA. Emeritus Professor, University of Sydney. Thanks to:. Statistical Society of Australia, NSW Branch, for inviting me to give this lecture. Duncan Young, . error and bias.  . Katie Harron. October 2014. UCL Institute of Child Health. k.harron@ucl.ac.uk.  . Match status. Match. (pair from same individual). Non-match. (pair from different individuals) . Motor Vehicle Injury Data Linkage Challenges. Jennifer Mathieu, PhD, Mike Fulk, Aileen Prior, Liz Richerson, Keith Miller, PhD; MITRE. Erica Spies, PhD; Centers for Disease Control and Prevention (CDC). Quan. &. Eliseo Gillamac. February 5, 2015. 2. What is Jurisdictional Change?. A jurisdictional change occurs when a taxing entity’s boundaries changes.. 3. Types of Jurisdictional Changes:. Annexation . Case Studies from the Data Linkage Program. Lisa B. Mirel. Board of Scientific Counselors. May 19, 2021. Introduction. Linking data is a powerful mechanism to provide policy relevant information in an efficient way. through Data Linkages. Lisa B. Mirel. NCHS Board of Scientific Counselors. May 26, 2022. Overview. NCHS Data Linkage Program. Data Modernization Initiative. Linking to New Sources of Data. Evaluating Linkage Methodologies. What would a safe and effective data linkage system look like?. July 2018. Catherine Bromley, Kerstin Hinds, Jo Mulligan and Job de Roij. Why are we interested in data linkage?. Statistics add . value. Lisa B. Mirel. Board of Scientific Counselors. January 9, 2020. Introduction. Proposing to use an enhanced algorithm and document changes with the next release of the linked mortality data for all NCHS surveys (expected release date Q3 2020) . III: Collaborative . Modelling. in Practice. October. 28, 2021. Developing. . tools. . for. . model. . linkage. & . cross-sectoral. . scenario. . analysis. Lessons. . learned. in . the. Krista Park. US Census Bureau. Center for Optimization and Data Science. Presentation for . FEDCASIC 2023. 1. Disclaimers. This presentation is released to inform interested parties of research and research requirements and to encourage discussion of a work in progress. Any views expressed are those of the authors and not those of the U.S. Census Bureau. . platform . e.g. local server, . SURE / SRAE. De-identified linked NSW Health Data . content variables. Cohort Definition. Description. Cases.  . Controls . (if relevant).  . External Cohort(s), with External Data Linkage Facility(. Peter W. F. Smith. Outline. The Administrative Data Research Network. The Administrative Data Research Centre for England. Guidance for Information about Linking Data sets. Record Linkage. Survey Representativeness . Linkage and linkage disequilibrium. Demonstration of software (. FamLink. ). Tutorials and exercises.  . Statistical inference for expanded marker panels (Part 2: “Large” panels) (10-12am). Technologies. Donald W. Rowe, PhD. Director Office of Public Health Practice, University at Buffalo, State University of New York. Paul Pettit, MSL Public Health Director. Genesee and Orleans County. Background. Programmatic and fiscal environment.