HRS Bibliography

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Nead KT, Li A, Wehner MR, et al. Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals. Human Molecular Genetics. 2015;24(12):3582-3594. doi:10.1093/hmg/ddv097.
Nead KT, Li A, Wehner MR, et al. Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals. Human Molecular Genetics. 2015;24(12):3582-3594. doi:10.1093/hmg/ddv097.
Nead KT, Li A, Wehner MR, et al. Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals. Human Molecular Genetics. 2015;24(12):3582-3594. doi:10.1093/hmg/ddv097.
Wolinsky FD, Bentler SE, Liu L, et al. Continuity of care with a primary care physician and mortality in older adults. J Gerontol A Biol Sci Med Sci. 2010;65(4):421-8. doi:10.1093/gerona/glp188.
http://www.ncbi.nlm.nih.gov/pubmed/19995831?dopt=Abstract
Wolinsky FD, Bentler SE, Liu L, et al. Continuity of care with a primary care physician and mortality in older adults. J Gerontol A Biol Sci Med Sci. 2010;65(4):421-8. doi:10.1093/gerona/glp188.
http://www.ncbi.nlm.nih.gov/pubmed/19995831?dopt=Abstract
Wolinsky FD, Bentler SE, Liu L, et al. Continuity of care with a primary care physician and mortality in older adults. J Gerontol A Biol Sci Med Sci. 2010;65(4):421-8. doi:10.1093/gerona/glp188.
http://www.ncbi.nlm.nih.gov/pubmed/19995831?dopt=Abstract
Wilkinson LR, Ferraro KF, Kemp BR. Contextualization of Survey Data: What Do We Gain and Does It Matter?. Research in Human Development. 2017;14(3):234-252. doi:10.1080/15427609.2017.1340049.
McArdle JJ. Contemporary Challenges of Longitudinal Measurement Using HRS Data. In: Walford G, Tucker E, Viswanathan M, eds. The Sage Handbook of Measurement. The Sage Handbook of Measurement. London: Sage Publications; 2009. doi:https://dx.doi.org/10.4135/9781446268230.n26.
Levine ME, Crimmins EM, Weir DR, Cole SW. Contemporaneous Social Environment and the Architecture of Late-Life Gene Expression Profiles. American Journal of Epidemiology. 2017;186(5):503-509. doi:10.1093/aje/kwx147.
http://www.ncbi.nlm.nih.gov/pubmed/28911009?dopt=Abstract
Hurd MD, McFadden D, Chand H, Gan L, Merrill A, Roberts MEwing. Consumption and Saving Balances of the Elderly: Experimental Evidence on Survey Response Bias. In: Wise DA, ed. Frontiers in the Economics of Aging. Frontiers in the Economics of Aging. Chicago: Univ. of Chicago Press; 1998:353-387.
Hong G-S, White-Means SI. Consumer Preferences for Health Care Reform Options. Journal of Consumer Affairs. 1999;33(2):237-53.
Wan X, Lighthall NR, Xie R. Consistent and robust predictors of Internet Use among older adults over time identified by machine learning. Computers in Human Behavior. 2022;137:107413. doi:https://doi.org/10.1016/j.chb.2022.107413.
Ware EB, Faul J, Mitchell C, Bakulski KM. Considering the APOE locus in Alzheimer's disease polygenic scores in the Health and Retirement Study: a longitudinal panel study. BMC Medical Genomics. 2020;13(1):164. doi:10.1186/s12920-020-00815-9.
Smith JP. Consequences and Predictors of New Health Events. In: Wise DA, ed. Analyses in the Economics of Aging. Analyses in the Economics of Aging. Chicago: University of Chicago Press; 2005.
Hill PL, Weston SJ, Jackson JJ. Connecting Social Environment Variables to the Onset of Major Specific Health Outcomes. Psychology and Health. 2014;29(7):753-767. doi:10.1080/08870446.2014.884221.
Turvey CL, Carney C, Arndt S, Wallace RB, Herzog AR. Conjugal loss and syndromal depression in a sample of elders aged 70 years or older. Am J Psychiatry. 1999;156(10):1596-601. doi:10.1176/ajp.156.10.1596.
http://www.ncbi.nlm.nih.gov/pubmed/10518172?dopt=Abstract
Ayanian JZ, Covinsky KE, Landon BE, McCarthy EP, Wee CC, Steinman MA. Conducting High-Value Secondary Dataset Analysis: An Introductory Guide and Resources. Journal of General Internal Medicine. 2011;26(8):920-929. doi:10.1007/s11606-010-1621-5.
Wolinsky FD, Jones MP, Ullrich FA, Lou Y, Wehby GL. The Concordance of Survey Reports and Medicare Claims in a Nationally Representative Longitudinal Cohort of Older Adults. Medical Care. 2014;52(5):462-468. doi:10.1097/MLR.0000000000000120.
Wolinsky FD, Jones MP, Ullrich FA, Lou Y, Wehby GL. The Concordance of Survey Reports and Medicare Claims in a Nationally Representative Longitudinal Cohort of Older Adults. Medical Care. 2014;52(5):462-468. doi:10.1097/MLR.0000000000000120.
Hudomiet P, Willis RJ. Computerization, obsolescence and the length of working life. Labour Economics. 2022;77:102005. doi:https://doi.org/10.1016/j.labeco.2021.102005.
Higgins-Chen AT, Thrush KL, Wang Y, et al. A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking. Nature Aging. 2022;2:644–661. doi:10.1038/s43587-022-00248-2.
Higgins-Chen AT, Thrush KL, Wang Y, et al. A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking. Nature Aging. 2022;2:644–661. doi:10.1038/s43587-022-00248-2.
Wei MY, Luster JE, Chan C-L, Min LC. Comprehensive review of ICD-9 code accuracies to measure multimorbidity in administrative data. BMC Health Services Research. 2020;20. doi:10.1186/s12913-020-05207-4.
Poterba JM, Venti SF, Wise DA. The Composition and Draw-down of Wealth in Retirement. Cambridge, MA: National Bureau of Economic Research; 2011. doi:10.3386/w17536.
Chao Y-S, Wu C-J, Wu H-C, et al. Composite diagnostic criteria are problematic for linking potentially distinct populations: the case of frailty. Scientific Reports. 2020;10(1). doi:10.1038/s41598-020-58782-1.