family-based association tests;
FBATs;
FBAT-logrank;
FBAT-Wilcoxon;
D O I:
10.1002/sim.1707
中图分类号:
Q [生物科学];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
In this paper, we discuss family-based association test (FBATs) relating genetic data to survival and time-to-onset data. We show how the standard logrank and Wilcoxon statistics can be used with family data to develop tests of association. We prove that the FBAT-logrank approach can be identical to the proportional hazard approach discussed in Mokliatchouk et al. (2000). Further, using simulation studies, we compare the power of the logrank, Wilcoxon and an approach developed for censored exponential data (Euro J Hum Gen 2001; 9:301-306). Based on the results of the simulation study, we suggest rules of thumb about which statistics to use in a given situation. An application of all three tests to an Alzheimer study illustrates the practical relevance of our discussion. Copyright (C) 2004 John Wiley Sons, Ltd.
机构:
Univ Bonn, Inst Med Stat & Genet Epidemiol, Bonn, Germany
Univ Calif Los Angeles, Dept Human Genet, Los Angeles, CA USA
Univ Calif Los Angeles, Dept Biostat, Los Angeles, CA USAUniv Bonn, Inst Med Stat & Genet Epidemiol, Bonn, Germany
Horvath, Steve
Xu, Xin
论文数: 0引用数: 0
h-index: 0
机构:
Harvard Sch Publ Hlth, Program Populat Genet, Boston, MA USAUniv Bonn, Inst Med Stat & Genet Epidemiol, Bonn, Germany
Xu, Xin
Laird, Nan M.
论文数: 0引用数: 0
h-index: 0
机构:
Harvard Sch Publ Hlth, Dept Biostat, Boston, MA USAUniv Bonn, Inst Med Stat & Genet Epidemiol, Bonn, Germany
机构:
Univ Bonn, Inst Med Stat & Genet Epidemiol, Bonn, Germany
Univ Calif Los Angeles, Dept Human Genet, Los Angeles, CA USA
Univ Calif Los Angeles, Dept Biostat, Los Angeles, CA USAUniv Bonn, Inst Med Stat & Genet Epidemiol, Bonn, Germany
Horvath, Steve
Xu, Xin
论文数: 0引用数: 0
h-index: 0
机构:
Harvard Sch Publ Hlth, Program Populat Genet, Boston, MA USAUniv Bonn, Inst Med Stat & Genet Epidemiol, Bonn, Germany
Xu, Xin
Laird, Nan M.
论文数: 0引用数: 0
h-index: 0
机构:
Harvard Sch Publ Hlth, Dept Biostat, Boston, MA USAUniv Bonn, Inst Med Stat & Genet Epidemiol, Bonn, Germany