HRS Bibliography

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Choi NG, Bohman TM. Predicting the changes in depressive symptomatology in later life: how much do changes in health status, marital and caregiving status, work and volunteering, and health-related behaviors contribute?. J Aging Health. 2007;19(1):152-77. doi:10.1177/0898264306297602.
Geiger JR, Wilks SE, Livermore MM. Predicting SNAP Participation in Older Adults: Do Age Categorizations Matter?. Educational Gerontology. 2014;40(12):932-946. doi:10.1080/03601277.2014.912837.
Blue L, Gill L, Faul JD, Bradway K, Stapleton D. Predicting Receipt of Social Security Administration Disability Benefits Using Biomarkers and Other Physiological Measures: Evidence From the Health and Retirement Study. Journal of Aging and Health. 2019;31(4):555-579. doi:10.1177/0898264317737893.
Leaf DErmini, Tysinger B, Goldman DP, Lakdawalla D. Predicting quantity and quality of life with the Future Elderly Model. Health Economics. 2020. doi:10.1002/hec.4169.
Waddell EL, Jacobs-Lawson JM. Predicting positive well-being in older men and women. The International Journal of Aging and Human Development. 2010;70(3):181-197. doi:10.2190/AG.70.3.a.
Banaszak-Holl J, A. Fendrick M, Foster NL, et al. Predicting Nursing Home Admission: Estimates from a seven-year follow-up of a nationally representative sample of older Americans. Alzheimer Disease and Associated Disorders. 2004;18(2):83-89.
Puterman E, Weiss J, Hives BA, et al. Predicting mortality from 57 economic, behavioral, social, and psychological factors. Proceedings of the National Academy of Sciences. 2020. doi:10.1073/pnas.1918455117.
Boveda I, Metz AJ. Predicting End-of-Career Transitions for Baby Boomers Nearing Retirement Age. The Career Development Quarterly. 2016;64(2):153 - 168. doi:10.1002/cdq.2016.64.issue-210.1002/cdq.12048.
Hill NL, Mogle J, Bell TReed, Bhargava S, Wion RK, Bhang I. Predicting current and future anxiety symptoms in cognitively intact older adults with memory complaints. International Journal of Geriatric Psychiatry. 2019;34(12):1874-1882. doi:10.1002/gps.5204.
Aschwanden D, Aichele S, Ghisletta P, et al. Predicting Cognitive Impairment and Dementia: A Machine Learning Approach. Journal of Alzheimer's disease : JAD. 2020;75(3):717-728. doi:10.3233/JAD-190967.
Cruz M, Covinsky KE, Widera EW, Stijacic-Cenzer I, Lee SJ. Predicting 10-year mortality for older adults. JAMA. 2013;309(9):874-6. doi:10.1001/jama.2013.1184.
Bobo JKay, Greek AA, Klepinger DH, Herting JR. Predicting 10-year alcohol use trajectories among men age 50 years and older. Am J Geriatr Psychiatry. 2013;21(2):204. doi:10.1097/JGP.0b013e3182423b4b.
Giustinelli P, Manski CF, Molinari F. Precise or Imprecise Probabilities? Evidence from Survey Response on Late-onset Dementia. National Bureau of Economic Research Working Paper Series. 2019;No. 26125. doi:10.3386/w26125.PDF icon w26125.pdf (535.1 KB)
Barsky R, Bound J, Charles KK, Lupton JP. A Precise Characterization of The Black-White Wealth Gap. University of Michigan; 2001.
Yilmazer T, Scharff RL. Precautionary Savings Against Health Risks: Evidence From the Health and Retirement Study. Research on Aging. 2013;36(2):180-206. doi:10.1177/0164027512473487.
Lusardi A. Precautionary Saving and the Accumulation of Wealth. Dartmouth College; 2000.
Donnelly R. Precarious Work, Marital Quality, and Divorce: A Gendered Dyadic Analysis of Aging Couples. Innovation in Aging. 2020;4(Suppl 1):605 . doi:10.1093/geroni/igaa057.2043.
Barcelo H, Faul JD, Crimmins EM, Thyagarajan B. A Practical Cryopreservation and Staining Protocol for Immunophenotyping in Population Studies. Current Protocols in Cytometry. 2018;84(1):e35. doi:10.1002/cpcy.35.
Bronshtein G, Scott JS, Shoven JB, Slavov SNataraj. The Power of Working Longer. Cambridge, MA: National Bureau of Economic Research; 2018. doi:10.3386/w24226.
Lee Y. Poverty Transitions for the Elderly. 2009:Ph.D.
Poverty report links wealth to life expectancy. Prince George Citizen. Published 2019.PDF icon ProQuestDocuments-2019-09-30.pdf (208.67 KB)
Bernstein SFae, Rehkopf D, Tuljapurkar S, Horvitz CC. Poverty dynamics, poverty thresholds and mortality: An age-stage Markovian model. Komarova NL, ed. PLOS ONE. 2018;13(5):e0195734. doi:10.1371/journal.pone.0195734.
Chopik WJ, Wimer C, Betson DM, Manfield L. Poverty among the aged population: The role of out-of-pocket medical expenditures and annuitized assets in supplemental poverty measure estimates. 2018:47-75.
Gawronski KAB, Kim ES, Miller LE. Potentially traumatic events and serious life stressors are prospectively associated with frequency of doctor visits and overnight hospital visits. Journal of Psychosomatic Research. 2014;77(2):90-96. doi:10.1016/j.jpsychores.2014.05.009.
Dougherty DD. Potential to Privately Pay for Long-Term Care Services. 2000.