HRS Bibliography

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Samwick AA, Wise DA. Option Value Estimation with HRS Data. In: Ogura S, Tachibanaki T, Wise DA, eds. Labor Markets and Firm Benefit Policies in Japan and the United States. Labor Markets and Firm Benefit Policies in Japan and the United States. Chicago: University of Chicago Press; 2003:205-228.
Sanchez-Arias R, Batista RW. Unsupervised Learning on the Health and Retirement Study using Geometric Data Analysis. In: 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA). 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA). Boca Raton, FL, USA: IEEE; 2019. doi:10.1109/ICMLA.2019.00063.
Sanchez-Niubo A, Forero CG, Wu Y-T, et al. Development of a common scale for measuring healthy ageing across the world: results from the ATHLOS consortium. International Journal of Epidemiology. 2021;50(3):880-892. doi:10.1093/ije/dyaa236.
Sanchez-Niubo A, Egea-Cortés L, Olaya B, et al. Cohort Profile: The Ageing Trajectories of Health - Longitudinal Opportunities and Synergies (ATHLOS) project. International Journal of Epidemiology. 2019;48(4):1052-1053i. doi:10.1093/ije/dyz077.
Sanguinetti TP. Decision-Making in Health Insurance Markets. Philosophy. 2020;Doctor of Philosophy.
Sanses TVD, Schiltz NK, Couri BM, et al. Functional status in older women diagnosed with pelvic organ prolapse. Am J Obstet Gynecol. 2016;214(5):613.e1-7. doi:10.1016/j.ajog.2015.11.038.
http://www.ncbi.nlm.nih.gov/pubmed/26704893?dopt=Abstract
Sanses TVD. Functional Status and Muscle Evaluation in Older Women with Urinary Incontinence. Epidemiology and Preventive Medicine. 2019;M.S.:103.
Santiago AM, Muschkin CG. Disentangling the effects of disability status and gender on the labor supply of Anglo, black, and Latino older workers. Gerontologist. 1996;36(3):299-310. doi:10.1093/geront/36.3.299.
http://www.ncbi.nlm.nih.gov/pubmed/8682328?dopt=Abstract
Sanz-de-Galdeano A, Terskaya A, Upegui A. Association of a Genetic Risk Score with BMI along the Life-Cycle: Evidence from Several US Cohorts. Bonn, Germany: IZA Institute of Labor Economics; 2020.
Sanz-de-Galdeano A, Terskaya A, Upegui A. Association of a genetic risk score with BMI along the life-cycle: Evidence from several US cohorts. PLoS One. 2020;15(9):e0239067. doi:10.1371/journal.pone.0239067.
http://www.ncbi.nlm.nih.gov/pubmed/32941506?dopt=Abstract
Sanzenbacher GT, Sass SA, Gillis CM. How job changes affect retirement timing by socioeconomic status. Boston: Center for Retirement Research at Boston College; 2017.
Sanzenbacher GT, Belbase A. Cognitive Impairment and Social Security’s Representative Payee Program. Center for Retirement Research at Boston College; 2016.
Sanzenbacher GT, Wu AYanyuan, Rutledge MS. The Impact of Temporary Assistance Programs on the Social Security Claiming Age. Chestnut Hill, MA: Center for Retirement Research at Boston College; 2015:1-331.
Sargent-Cox KA, Anstey KJ, Kendig H, Skladzien E. Determinants of retirement timing expectations in the United States and Australia: a cross-national comparison of the effects of health and retirement benefit policies on retirement timing decisions. J Aging Soc Policy. 2012;24(3):291-308. doi:10.1080/08959420.2012.676324.
http://www.ncbi.nlm.nih.gov/pubmed/22720888?dopt=Abstract
Sarpong E. Essays in Labor Economics: Alcohol consumption and socioeconomic outcomes. Economics. 2007;Doctor of Philosophy.
Sass SA, Sun W, Webb A. When Should Married Men Claim Social Security Benefits?. Boston: Center for Retirement Research at Boston College; 2008.
Sasson I, Umberson D. Widowhood and depression: new light on gender differences, selection, and psychological adjustment. The journals of gerontology. Series B, Psychological sciences and social sciences. 2014;69(1):135.
Sathyan S, Wang T, Ayers E, Verghese J. Genetic basis of motoric cognitive risk syndrome in the Health and Retirement Study. Neurology. 2019;92(13):e1427-e1434. doi:10.1212/WNL.0000000000007141.
http://www.ncbi.nlm.nih.gov/pubmed/30737336?dopt=Abstract
Sauerteig MR, Ferraro KF, Bauldry S. Life Course Stressors and Functional Limitations in Later Life among White, Black, and Hispanic Adults: Deleterious, Hardening, or Benign?. The Journals of Gerontology, Series B . 2022;77(1):249-259. doi:10.1093/geronb/gbab066.
Savage JE, Jansen PR, Stringer S, et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nature Genetics. 2018;50(7):912 - 919. doi:10.1038/s41588-018-0152-6.
Savva GM, Maty SC, Setti A, Feeney J. Cognitive and Physical Health of the Older Populations of England, the United States, and Ireland: International Comparability of The Irish Longitudinal Study on Ageing. Journal of the American Geriatrics Society. 2013;61:S291-S298. doi:http://dx.doi.org/10.1111/jgs.12196.
Saxena A. Effect of Retirement on Health and Mortality. Public Health. 2018;Master of Science:231.
Schaller J, Eck C. Family Support in Hard Times: Dynamics of Intergenerational Exchange after Adverse Events. Cambridge, MA: National Bureau of Economic Research; 2020. doi:10.3386/w28295.
Schaller J, Eck C. Adverse Life Events and Intergenerational Transfers. W.E. Upjohn Institute for Employment Research; 2019. doi:10.17848/wp19-313.
Schapmire TJ. Emotional distress in older adults with cancer: A multilevel longitudinal study. Social Work. 2012;Ph.D. doi:10.18297/etd/1269.