{"id":184,"date":"2026-08-20T01:51:30","date_gmt":"2026-08-20T01:51:30","guid":{"rendered":"https:\/\/sites.nd.edu\/yang-c-yang\/?page_id=184"},"modified":"2026-08-26T19:52:03","modified_gmt":"2026-08-26T19:52:03","slug":"new-methodologies-for-population-research-on-aging","status":"publish","type":"page","link":"https:\/\/sites.nd.edu\/yang-c-yang\/new-methodologies-for-population-research-on-aging\/","title":{"rendered":"New Methodologies for Population Research on Aging"},"content":{"rendered":"\n

Studies of time-related change are key to understanding the process and dynamics of aging but are often subject to data and methodological limitations. I have been continuously engaged in the development of new statistical methodologies to address these limitations in various directions. These methods have innovated ways to assemble and analyze diverse forms of temporally ordered data. Recent empirical applications of these methods have produced new evidence for long-standing questions and suggested new questions to ask in interdisciplinary population research on aging.<\/p>\n\n\n\n

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Age-Period-Cohort (APC) Analysis<\/a><\/strong>
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Data Linkage Methods<\/a><\/strong><\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n\n\n


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