MULTILEVEL MODELING IN GENETIC ANALYSIS

$294,555P41FY2001RRNIH

Case Western Reserve University, Cleveland OH

Investigators

Linked publications & trials

Paper 31865790 Paper 28980238 Paper 27792787 Paper 27467133 Paper 27306940 Paper 27172222 Paper 27027516 Paper 26881833 Paper 26697508 Paper 26203966 Paper 26169204 Paper 26063907 Paper 25904649 Paper 25737442 Paper 25552592 Paper 25376640 Paper 25316108 Paper 25096241 Paper 25050884 Paper 24583363 Paper 24347668 Paper 24126174 Paper 24013571 Paper 23883829 Paper 23739559 Paper 23712436 Paper 23629934 Paper 23569188 Paper 23524007 Paper 23485345 Paper 23446634 Paper 23434219 Paper 23280346 Paper 23154503 Paper 23110055 Paper 22984439 Paper 22809306 Paper 22738121 Paper 22648939 Paper 22473018 Paper 22469955 Paper 22426781 Paper 22307703 Paper 22307701 Paper 22307694 Paper 22307690 Paper 22291100 Paper 22253211 Paper 22215178 Paper 22189466 Paper 22126647 Paper 22045927 Paper 22045388 Paper 22022419 Paper 22017397 Paper 21930616 Paper 21925394 Paper 21923410 Paper 21920414 Paper 21805821 Paper 21738479 Paper 21731658 Paper 21708019 Paper 21685074 Paper 21626137 Paper 21594893 Paper 21571680 Paper 21523954 Paper 21509519 Paper 21454968 Paper 21398654 Paper 21381436 Paper 21364090 Paper 21358712 Paper 21354459 Paper 21297019 Paper 21283783 Paper 21247474 Paper 21212683 Paper 21207764 Paper 21181895 Paper 21150212 Paper 20861866 Paper 20807177 Paper 20623172 Paper 20588308 Paper 20551049 Paper 20549515 Paper 20538960 Paper 20529905 Paper 20414195 Paper 20401947 Paper 20358593 Paper 20309765 Paper 20299368 Paper 20200424 Paper 20185150 Paper 20122219 Paper 20081511 Paper 20075193

Abstract

Hierarchical modeling is a statistical approach that generally outperforms a conventional (one-level) analysis by using multiple level models. Specifically, hierarchical models can provide more reasonable and stable parameter estimates than conventional analytical approaches. In addition, this technique deals with problems of multiple comparisons and allows one to adequately model multilevel data within a hierarchical framework. In this project we are extending this technique to cancer research and genetic epidemiology through a combination of application, methodological development, and simulation studies. In particular, we are advancing this valuable technique by showing how one can use hierarchical modeling in genetic epidemiologic research to evaluate multiple candidate genes, and by providing to the scientific community software for undertaking hierarchical modeling. [unreadable])

View original record on NIH RePORTER →