HRS Bibliography

Bibliography Search
Export 595 results:
Filters: First Letter Of Title is P  [Clear All Filters]

Journal Article

Choi NG. Potential Consequences of Raising the Social Security Eligibility Age on Low-Income Older Workers. Journal of Aging and Social Policy. 2000;11(4):15-39. doi:10.1300/J031v11n04_04.
Hurd MD, Smith JP, Zissimopoulos JM. The Potential Effects of Obesity on Social Security Claiming Behavior and Retirement Benefits. J Gerontol B Psychol Sci Soc Sci. 2018;73(4):723-732. doi:10.1093/geronb/gbw016.
http://www.ncbi.nlm.nih.gov/pubmed/27044665?dopt=Abstract
Ayanian JZ, Meara E, McWilliams JM. Potential Enhancements to Data on Health Insurance, Health Services, and Medicare in the Health and Retirement Study. Forum for Health Economics and Policy. 2011;14(3):Article 3. doi:10.2202/1558-9544.1262.
Raykov T, Gorelick PB, Zajacova A, Marcoulides GA. On the potential of discrete time survival analysis using latent variable modeling: An application to the study of the vascular depression hypothesis. Structural Equation Modeling: A Multidisciplinary Journal. 2017:1 - 10. doi:10.1080/10705511.2017.1315305.
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.
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.
Curnutt G, Sun Q, Guillemette MA. Practical Applications of Post-Retirement Labor and Non-Retirement Risky Asset Allocation. Practical Applications. 2021;9(2). doi:10.3905/pa.2021.pa473.
Barcelo H, Faul J, 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.
http://www.ncbi.nlm.nih.gov/pubmed/30040214?dopt=Abstract
Panikkar D, Vivek S, Crimmins E, Faul J, Langa KM, Thyagarajan B. Pre-Analytical Variables Influencing Stability of Blood-Based Biomarkers of Neuropathology. Journal of Alzheimer's Disease. Forthcoming. doi:10.3233/JAD-230384.
Donnelly R. Precarious Work in Midlife: Long-Term Implications for the Health and Mortality of Women and Men. Journal of Health and Social Behavior. 2022;63(1):142-158. doi:10.1177/00221465211055090.
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.
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.
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)
Giustinelli P, Manski CF, Molinari F. Precise or Imprecise Probabilities? Evidence from Survey Response Related to Late-onset Dementia. Journal of the European Economic Association. 2022;20(1):187-221. doi:10.1093/jeea/jvab023.
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.
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.
http://www.ncbi.nlm.nih.gov/pubmed/23462780?dopt=Abstract
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.
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.
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.
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.
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.
Waddell EL, Jacobs-Lawson JM. Predicting positive well-being in older men and women. Int J Aging Hum Dev. 2010;70(3):181-97. doi:10.2190/AG.70.3.a.
http://www.ncbi.nlm.nih.gov/pubmed/20503804?dopt=Abstract
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.
Blue L, Gill L, Faul J, 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.
http://www.ncbi.nlm.nih.gov/pubmed/29254420?dopt=Abstract
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.