HRS Bibliography

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Journal Article

Kilpeläinen TO, Bentley AR, Noordam R, et al. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nature Communications. 2019;10(1):376. doi:10.1038/s41467-018-08008-w.
Kilpeläinen TO, Bentley AR, Noordam R, et al. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nature Communications. 2019;10(1):376. doi:10.1038/s41467-018-08008-w.
Kilpeläinen TO, Bentley AR, Noordam R, et al. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nature Communications. 2019;10(1):376. doi:10.1038/s41467-018-08008-w.
Kilpeläinen TO, Bentley AR, Noordam R, et al. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nature Communications. 2019;10(1):376. doi:10.1038/s41467-018-08008-w.
Kilpeläinen TO, Bentley AR, Noordam R, et al. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nature Communications. 2019;10(1):376. doi:10.1038/s41467-018-08008-w.
Sun D, Richard M, Musani SK, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. Human Genetics and Genomics Advances. 2021;2(1):100013. doi:10.1016/j.xhgg.2020.100013.
Sun D, Richard M, Musani SK, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. Human Genetics and Genomics Advances. 2021;2(1):100013. doi:10.1016/j.xhgg.2020.100013.
Sun D, Richard M, Musani SK, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. Human Genetics and Genomics Advances. 2021;2(1):100013. doi:10.1016/j.xhgg.2020.100013.
Sun D, Richard M, Musani SK, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. Human Genetics and Genomics Advances. 2021;2(1):100013. doi:10.1016/j.xhgg.2020.100013.
Sun D, Richard M, Musani SK, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. Human Genetics and Genomics Advances. 2021;2(1):100013. doi:10.1016/j.xhgg.2020.100013.
Sun D, Richard M, Musani SK, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. Human Genetics and Genomics Advances. 2021;2(1):100013. doi:10.1016/j.xhgg.2020.100013.
Domingue BW, Belsky DW, Harrati A, Conley DC, Weir DR, Boardman JD. Mortality selection in a genetic sample and implications for association studies. International Journal of Epidemiolpgy. 2017;46(4). doi:10.1093/ije/dyx041.
R. Konetzka T, He D, Dong J, Nyman JA. Moral hazard and long-term care insurance. The Geneva Papers on Risk and Insurance - Issues and Practice. 2019;44(2):231–251. doi:10.1057/s41288-018-00119-1.
Hurd MD, Martorell P, Delavande A, Mullen KJ, Langa KM. Monetary costs of dementia in the United States. N Engl J Med. 2013;368(14):1326-34. doi:10.1056/NEJMsa1204629.
http://www.ncbi.nlm.nih.gov/pubmed/23550670?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.
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.
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.
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.
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.
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.
Pare G, Mao S, Deng WQ. A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics. Sci Rep. 2016;6:27644. doi:10.1038/srep27644.
http://www.ncbi.nlm.nih.gov/pubmed/27273519?dopt=Abstract
A Erzurumluoglu M, Liu M, Jackson VE, et al. Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. Molecular Psychiatry. 2020;25(10):2392-2409. doi:10.1038/s41380-018-0313-0.
A Erzurumluoglu M, Liu M, Jackson VE, et al. Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. Molecular Psychiatry. 2020;25(10):2392-2409. doi:10.1038/s41380-018-0313-0.
A Erzurumluoglu M, Liu M, Jackson VE, et al. Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. Molecular Psychiatry. 2020;25(10):2392-2409. doi:10.1038/s41380-018-0313-0.
A Erzurumluoglu M, Liu M, Jackson VE, et al. Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. Molecular Psychiatry. 2020;25(10):2392-2409. doi:10.1038/s41380-018-0313-0.