HRS Bibliography

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Journal Article

Vable AM, Kiang MV, Basu S, et al. Military Service, Childhood Socio-Economic Status, and Late-Life Lung Function: Korean War Era Military Service Associated with Smaller Disparities. Military Medicine. 2018. doi:10.1093/milmed/usx196.
http://www.ncbi.nlm.nih.gov/pubmed/29509934?dopt=Abstract
MacLean A, Edwards RD. Military service, combat exposure, and health in the later lives of US men . Longitudinal and Life Course Studies. 2017;8(2):122-137. doi:10.14301/llcs.v8i2.427.
Zhang S, Li H, Engström G, et al. Milk intake, lactase persistence genotype, plasma proteins and risks of cardiovascular events in the Swedish general population. Eur J Epidemiol. 2023;38(2):211-224. doi:10.1007/s10654-022-00937-7.
Blanchett D. Minding the Gap in Subjective Mortality Estimates. The Journal of Retirement. 2021;9(1). doi:10.3905/jor.2021.1.093.
Jackson JS, Lockery SA, F. Juster T. Minority perspectives from the Health and Retirement Study. Introduction: health and retirement among ethnic and racial minority groups. Gerontologist. 1996;36(3):282-4. doi:10.1093/geront/36.3.282.
http://www.ncbi.nlm.nih.gov/pubmed/8682326?dopt=Abstract
B. Bernheim D, Forni L, Gokhale J, Kotlikoff LJ. The Mismatch Between Life Insurance Holdings and Financial Vulnerabilities: Evidence from the Health and Retirement Study. American Economic Review. 2003;93(1):354-365. doi:10.1257/000282803321455340.
Gustman AL, Steinmeier TL, Tabatabai N. Mismeasurement of pensions before and after retirement: the mystery of the disappearing pensions with implications for the importance of Social Security as a source of retirement support. Journal of Pension Economics and Finance. 2014;13(1):1-26.
Wang L, Shen H, Liu H, Guo G. Mixture SNPs effect on phenotype in genome-wide association studies. BMC Genomics. 2015;16:3. doi:10.1186/1471-2164-16-3.
http://www.ncbi.nlm.nih.gov/pubmed/25649116?dopt=Abstract
Mueller C, West JS. MOBILITY TRAJECTORIES, HEALTHCARE SATISFACTION, AND PERCEIVED DISABILITY DISCRIMINATION AMONG OLDER ADULTS. Innovation in Aging. 2019;3:S523-S524. doi:10.1093/geroni/igz038.1928.
Domingue BW, McCammon R, West BT, Langa KM, Weir DR, Faul J. The mode effect of web-based surveying on the 2018 HRS measure of cognitive functioning. J Gerontol B Psychol Sci Soc Sci. 2023. doi:10.1093/geronb/gbad068.
Faul J, Domingue B, Stenhaug B, West BT, Langa KM, Weir DR. MODE EFFECTS ON COGNITIVE FUNCTIONING ASSESSMENTS IN THE HEALTH AND RETIREMENT STUDY. Innovation in Aging. 2022;6(Suppl 1):163. doi:10.1093/geroni/igac059.652.
Hatfield LA, Favreault M, McGuire TG, Chernew ME. Modeling Health Care Spending Growth of Older Adults. Health Services Research. 2018;53:138-155. doi:10.1111/1475-6773.12640.
Domingue BW, Kanopka K, Mallard TT, Trejo S, Tucker-Drob EM. Modeling Interaction and Dispersion Effects in the Analysis of Gene-by-Environment Interaction. Behavior Genetics. 2022;52(1):56-64. doi:10.1007/s10519-021-10090-8.
Das K, Ghosh P, Daniels MJ. Modeling Multiple Time-Varying Related Groups: A Dynamic Hierarchical Bayesian Approach with an Application to the Health and Retirement Study. Journal of the American Statistical Association. 2021;116(534):558-568. doi:10.1080/01621459.2021.1886105.
Marshall GL, Ingraham B, Major J, Kahana E, Stansbury K. Modeling the impact of financial hardship and age on self-rated health and depressive symptoms pre/post the great recession. SSM - Population Health. 2022;18:101102. doi:https://doi.org/10.1016/j.ssmph.2022.101102.
Mayer A, Geiser C, Infurna FJ, Fiege C. Modelling and predicting complex patterns of change using growth component models: An application to depression trajectories in cancer patients. European Journal of Developmental Psychology. 2013;10(1):40-59. doi:10.1080/17405629.2012.732721.
Gulshan J, Khan A, M Islam A. Modelling Correlated Bivariate Binary Data: A Comparative View. Bulletin of the Malaysian Mathematical Sciences Society. 2022. doi:10.1007/s40840-022-01290-4.
Goulden R. Moderate Alcohol Consumption Is Not Associated with Reduced All-cause Mortality. The American Journal of Medicine. 2016;129(2):180 186.e4. doi:10.1016/j.amjmed.2015.10.013.
Herring D, Paulson D. Moderate alcohol use and apolipoprotein E-4 (ApoE-4): Independent effects on cognitive outcomes in later life. Journal of Clinical and Experimental Neuropsychology. 2018;40(4):326-337. doi:10.1080/13803395.2017.1343803.
http://www.ncbi.nlm.nih.gov/pubmed/28659024?dopt=Abstract
Andreyeva T, Sturm R, Ringel JS. Moderate and severe obesity have large differences in health care costs. Obes Res. 2004;12(12):1936-43. doi:10.1038/oby.2004.243.
http://www.ncbi.nlm.nih.gov/pubmed/15687394?dopt=Abstract
Li R, Dworkin RH, Chapman BP, et al. Moderate to severe chronic pain in later life: risk and resilience factors for recovery. The Journal of Pain. 2021;22(12):1657-1671. doi:10.1016/j.jpain.2021.05.007.
Choi SL, Wilmarth MJ. The Moderating Role of Depressive Symptoms Between Financial Assets and Bequests Expectation. Journal of Family and Economic Issues. 2019;40(3):498–510. doi:10.1007/s10834-019-09621-7.
Barnes-Farrell JL, Petery GA. The Moderating Role of Employment Status and Gender on Relationships Between Psychological Age and Health: A Two-Wave Cross-Lagged Panel Analysis of Data From the Health and Retirement Study. Ryan LH, ed. Work, Aging and Retirement. 2018;4(1):79-95. doi:10.1093/workar/wax019.
Shi Y, W Hooten M, Roberts RO, Warner DO. Modifiable risk factors for incidence of pain in older adults. Pain. 2010;151(2):366-371. doi:10.1016/j.pain.2010.07.021.
http://www.ncbi.nlm.nih.gov/pubmed/20696524?dopt=Abstract
Verghese J, Wang C, Allali G, Holtzer R, Ayers E. Modifiable Risk Factors for New-Onset Slow Gait in Older Adults. Journal of the American Medical Directors Association. 2016;17(5):421-425. doi:10.1016/j.jamda.2016.01.017.