HRS Bibliography

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Levine ME, Harrati A, Crimmins EM. Predictors and implications of accelerated cognitive aging. Biodemography and Social Biology. 2018;64(2):83-101. doi:10.1080/19485565.2018.1552513.
Lundin A, Leijon O, Vaez M, Hallgren M, Torgén M. Predictive validity of the Work Ability Index and its individual items in the general population. Scandinavian Journal of Public Health. 2017;45(4):350-356. doi:10.1177/1403494817702759.
Hurd MD, McGarry K. The Predictive Validity of Subjective Probabilities of Survival. The Economic Journal. 2002;112(482).
Elder TE. The predictive validity of subjective mortality expectations: evidence from the health and retirement study. Demography. 2013;50(2):569. doi:10.1007/s13524-012-0164-2.
Shen X, Yin F, Jiao C. Predictive Models of Life Satisfaction in Older People: A Machine Learning Approach. Int J Environ Res Public Health. 2023;20(3). doi:10.3390/ijerph20032445.
Chowdhury RI, M. Islam A. Predictive Models for Trajectory Risks Prediction from Repeated Ordinal Outcomes. Bulletin of the Malaysian Mathematical Sciences Society. Forthcoming. doi:10.1007/s40840-022-01277-1.
Chowdhury RI, M. Islam A. Prediction of Disease Status: Transition Model Approach for Repeated Measures. Pakistan Journal of Statistics . 2014;30(2):181-196.PDF icon PAKJSTAT.pdf (403.25 KB)
M. Islam A, Chowdhury RI. Prediction of disease status: A regressive model approach for repeated measures. Statistical Methodology. 2010;7(5):520-540. doi:https://doi.org/10.1016/j.stamet.2010.03.001.
Nye J. Prediction Model for Mortality May Inform Dementia Treatment in Older Adults.
Preisser JS, Moss K, Finlayson TL, Jones JA, Weintraub JA. Prediction Model Development and Validation of 12-Year Incident Edentulism of Older Adults in the United States. JDR Clinical & Translational Research. Forthcoming. doi:10.1177/23800844221112062.
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.
http://www.ncbi.nlm.nih.gov/pubmed/17215206?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.
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
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. 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
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.
Badolato L, Decter-Frain A, Irons NJ, et al. Predicting individual-level longevity with statistical and machine learning methods. Max Planck Institute; 2023. doi:10.4054/MPIDR-WP-2023-008.
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.
http://www.ncbi.nlm.nih.gov/pubmed/23462780?dopt=Abstract
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 Related to Late-onset Dementia. Journal of the European Economic Association. 2022;20(1):187-221. doi:10.1093/jeea/jvab023.
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)