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- Chapter 5 – Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications
- Chapter 6 – Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications
- Chapter 7 – Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications
- Chapter 8 – Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications
- Chapter 9 – Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications
- Integrative Data Analysis (IDA)
- Teaching
CV and Publications
Curriculum Vitae (PDF) 
Selected Publications: (*indicates senior authorship with equal weight to the first author; +indicates a current or former student or post-doc/fellow mentee)
2023 Yang, Yang Claire, Christine E. Walsh, Kaitlin Shartle, Rebecca C. Stebbins, Allison E. Aiello, Daniel W. Belsky, Kathleen Mullan Harris, Marianne Chanti-Ketterl, and Brenda L. Plassman. “An Early and Unequal Decline: Life Course Trajectories of Cognitive Aging in the United States.” Journal of Aging and Health: DOI: https://doi.org/10.1177/08982643231184593. PMCID: 37335551.
2022 Walsh, Christine E.+, Yang C. Yang, Katsuya Oi+, Allison E. Aiello, Daniel W. Belsky, Kathleen M. Harris, and Brenda L. Plassman. “Age Profiles of Cognitive Decline and Dementia in Late Life in the Aging, Demographics and Memory Study (ADAMS).” Journals of Gerontology, Series B: Social Sciences 77:1880-91. https://doi.org/10.1093/geronb/gbac038. PMCID: 35171992.
2022 Rebecca C. Stebbins+, Joanna Maselko, Yang C. Yang, Brenda Plassman, Jessie K. Edwards, Allison E. Aiello. “Lifecourse Traumatic Events and Cognitive Aging in the Health and Retirement Study.” American Journal of Preventive Medicine 63(5):818-826. https://doi.org/10.1016/j.amepre.2022.05.007. PMCID: 35798618.
2022 Shartle, Kaitlin+, Yang C. Yang, Laura S. Richman, Daniel W. Belsky, Allison E. Aiello, and Kathleen Mullan Harris. “Social Relationships, Wealth, and Cardiometabolic Risk: Evidence from a National Longitudinal Study of U.S. Older Adults.” Journal of Aging and Health 34(6-8):1048-1061. https://doi.org/10.1177/08982643221087807. PMCID: 35481380.
2022 Stebbins, Rebecca C.+, Yang C. Yang, Max Reason+, Allison E. Aiello, Daniel W. Belsky, Kathleen Mullan Harris, and Brenda L. Plassman. “Occupational Cognitive Stimulation, Socioeconomic Status, and Cognitive Functioning in Young Adulthood.” Social Science & Medicine – Population Health 17:101024. https://doi.org/10.1016/j.ssmph.2022.101024. PMCID: 8762043.
2022 Chanti-Ketterl, Marianne+, Rebecca C. Stebbins+, Hardeep K. Obhi+, Daniel W. Belsky, Brenda L. Plassman, and Yang C. Yang. “Sex Differences in the Association between Metabolic Dysregulation and Cognitive Aging: The Health and Retirement Study.” Journals of Gerontology: Medical Sciences 77(9):1827-1835. https://doi.org/10.1093/Gerona/glab285. PMCID: 34606593.
2021 Yang, Yang Claire, Christine E. Walsh+, Moira Johnson+, Dan Belsky, Max Reason+, Patrick Curran, Allison Aiello, Marianne Chanti-Ketterl, and Kathleen Mullan Harris. “Life Course Trajectories of Body Mass Index from Adolescence to Old Age: Racial and Educational Disparities.” Proceedings of the National Academy of Science 118(17):e2020167118. https://www.pnas.org/doi/full/10.1073/pnas.2020167118. PMCID: 8092468.
2020 Noah Snyder-Mackler, Joseph Robert Burger, Lauren Gaydosh, Dan Belsky, Grace A. Noppert+, Fernando A. Campos, Alessandro Bartolomucci, Yang Claire Yang, Allison E. Aiello, Angela O’Rand, Kathleen Mullan Harris, Carol A. Shively, Susan C. Alberts, and Jenny Tung. “Social Determinants of Health and Survival in Humans and Other Animals.” Science 368(6493), eaax9553. https://doi.org/10.1126/science.aax9553. PMCID: PMC7398600.
2020 Yang, Yang Claire, Courtney Boen+, Kristen Schorpp+, Moira Johnson+, and Kathleen Mullan Harris. “Socioeconomic Status and Biological Risks for Health and Illness Across the Life Course.” Journals of Gerontology: Social Sciences 75(3):613-624. https://doi.org/10.1093/geronb/gby108. PMCID: PMC7328029. – selected as Editor’s Choice feature article
2019 Zang, Emma, Hui Zheng, Yang Claire Yang, and Kenneth Land. “Recent Trends in U.S. Mortality in Early and Middle Adulthood: Race/Ethnic Disparities in Inter-Cohort Patterns.” International Journal of Epidemiology 48(3):934-944. https://doi.org/10.1093/ije/dyy255. PMCID: PMC6934031.
2018* Boen, Courtney+, David Barrow, Jeannette T. Bensen, Laura Farnan, Adrian Gerstel, Laura Hendrix, and Yang Claire Yang. “Social Relationships, Inflammation, and Cancer Survival.” Cancer Epidemiology, Biomarkers & Prevention 27(5):541-9. http://dx.doi.org/10.1158/1055-9965.EPI-17-0836. PMCID: PMC5932225. – Highlight of the issue.
2017 Yang, Yang Claire, Moira Johnson+, Courtney Boen+, Kristen Schorpp+, and Kathleen Mullan Harris. “Social Disparities in Biological Risk Factors of Cancer in Young Adulthood: Obesity, Inflammation, and Socio-behavioral Mechanisms.” American Journal of Preventive Medicine 53(3S1):S21-S29. PMCID: PMC5867534.
Age-Period-Cohort Analysis Home Page
The identification and estimation of distinct effects for age (A), time period (P), and birth cohort (C) on outcome variables or event rates of interest long has been a goal of analysis in demography, epidemiology, sociology, and other social sciences. The intrinsic difficulty of identifying and estimating these conceptually different effects also has been recognized for decades. This has given rise to the numerous methods and approaches to Age-Period-Cohort (APC) analysis, which sometimes is simply termed cohort analysis. Recently, there has been a revival of interest in the development of new statistical methods for APC analysis and in substantive applications thereof.
This section is dedicated to the presentation of citations to a number of classical publications on APC analysis and recent contributions to cohort analysis methods and substantive applications. They have been subsumed into the book titled “Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications” published by Chapman & Hall/CRC.
Longitudinal Integrative Data Analysis (IDA) Home Page
A major challenge in life course and aging research is the lack of prospective data that span the full life course for the study of age-related changes in life outcomes. My team has developed over the past few years new tools for addressing this problem. We used an extensive longitudinal life course research design and a novel application of integrative data analysis (IDA). The longitudinal IDA methodology offers a number of advantages over conventional single studies by combining and simultaneously analyzing multiple prospective studies based on the cohort sequential design.
This section shows an example of its application to a recent NIA-funded research project on cognitive aging and provides access to public use open source codes for interested users.
(Last updated in June, 2023)