HRS Bibliography

Bibliography Search
Export 324 results:
Filters: First Letter Of Title is M  [Clear All Filters]


Baidwan NKaur, Gerberich SGoodwin, Kim H, Ryan AD, Church T, Capistrant BD. A marginal structural model approach to analyse work-related injuries: An example using data from the Health and Retirement Study. Injury Prevention. 2020. doi:10.1136/injuryprev-2018-043124.
Altonji JG, Villanueva E, Department of Economics. The Marginal Propensity to Spend on Adult Children. New Haven, Connecticut, Yale University; 2004.
Altonji JG, Villanueva E. The Marginal Propensity to Spend on Adult Children. Cambridge, MA: The National Bureau of Economic Research; 2003. doi:10.3386/w9811.
Zubair S, Sinha SK. MARGINAL MODELS FOR LONGITUDINAL COUNT DATA WITH DROPOUTS. Journal of Statistical Research. 2020;54. doi:
Yu RP, Ellison NB, McCammon RJ, Langa KM. Mapping the Two Levels of Digital Divide: Internet Access and Social Network Site Adoption among Older Adults in the USA. Information, Communication and Society. 2016;19(10):1445-1464. doi:10.1080/1369118X.2015.1109695.
Snider M. Many in 50s Face Hard Years. USA Today. 1993:A1.
Span P. Many Americans will need long-term care. Most won’t be able to afford it. The New York Times. Published 2019.
Span P. Many Americans Try Retirement, Then Change Their Minds. The New York Times. Published 2018.
Delavande A, Willis RJ. Managing the Risk of Life. Ann Arbor, MI: Michigan Retirement and Disability Research Center, University of Michigan; 2007.
Browning C. Managing retirement resources: evidence from the HRS. 2013;PhD.
Huang ES. Management of diabetes mellitus in older people with comorbidities. BMJ. 2016;353:i2200. doi:10.1136/bmj.i2200.
Xu X, Jensen GA. Managed Care and the Near-Elderly: Effects of plan enrollment on functionality. Applied Economics. 2007;39(16):2027. doi:
Miller TR. Mammography Use among Older Women in the Asset and Health Dynamics Among the Oldest Old (AHEAD) Study. 2007.
Lu P, Kong D, Shelley M. Making the Decision to Move to a Nursing Home: Longitudinal Evidence From the Health and Retirement Study. Journal of Applied Gerontology. 2020. doi:
Hyland M. Making it Work: Transitions From Physically Demanding Employment in Advanced Age. Ithaca, NY: Cornell University; 2020.
Roberts MEwing. Making Ends Meet in a Social Context: Grandparent Childcare during the 2008 Recession, Debt of the Poor and Financial Innovation, and Relative Poverty's Effect on Election Outcomes. Economics. 2018;PhD:209.
Das A. Major discrimination experiences, education, and genes. Journal of Aging and Health. 2020;32(7-8):753-763. doi:10.1177/0898264319851661.
Mojtabai R, Olfson M. Major depression in community-dwelling middle-aged and older adults: prevalence and 2- and 4-year follow-up symptoms. Psychol Med. 2004;34(4):623-34. doi:10.1017/S0033291703001764.
Melville JL, Fan M-Y, Rau H, Nygaard IE, Katon WJ. Major depression and urinary incontinence in women: temporal associations in an epidemiologic sample. Am J Obstet Gynecol. 2009;201(5):490.e1-7. doi:10.1016/j.ajog.2009.05.047.
Xiang X, Leggett AN, Himle JA, Kales HC. Major Depression and Subthreshold Depression among Older Adults Receiving Home Care. American Journal of Geriatric Psychiatry. 2018;26(9):939-949. doi:10.1016/j.jagp.2018.05.001.
Hill PL, Beck ED, Jackson JJ. Maintaining Sense of Purpose Following Health Adversity in Older Adulthood: A Propensity Score Matching Examination. The Journals of Gerontology: Series B . 2021;76(8):1574-1579. doi:10.1093/geronb/gbab002.
Sevak P, Schmidt L. Macroeconomic Conditions and Updating of Expectations by Older Americans. Ann Arbor, MI: The University of Michigan, Michigan Retirement Research Center; 2011.
Pare G, Mao S, Deng WQ. A machine-learning heuristic to improve gene score prediction of polygenic traits. Scientific Reports. 2017;7(1):12665. doi:10.1038/s41598-017-13056-1.
Seligman B, Tuljapurkar S, Rehkopf D. Machine learning approaches to the social determinants of health in the Health and Retirement study. SSM Popul Health. 2018;4:95-99. doi:10.1016/j.ssmph.2017.11.008.