期刊論文

學年 101
學期 1
出版(發表)日期 2012-10-01
作品名稱 Robust methods for detecting familial aggregation of a quantitative trait in matched case-control family studies
作品名稱(其他語言)
著者 Wang, Jiun-yi; Chen, Li-ching; Lin, Hui-min
單位 淡江大學統計學系
出版者 Abingdon: Routledge
著錄名稱、卷期、頁數 Journal of Applied Statistics 39(10), 2097-2111
摘要 Assessing familial aggregation of a disease or its underlying quantitative traits is often undertaken as the first step in the investigation of possible genetic causes. When some major confounding variables are known and difficult to be quantified, the matched case–control family design provides an opportunity to eliminate biased results. In such a design, cases and matched controls are ascertained first, with subsequent recruitment of other members in their families. For the study of complex diseases, many continuously distributed quantitative traits or biomedical evaluations are of primary clinical and health significance, and distributions of these continuous outcomes are frequently skewed or non-normal. A non-normal distributed outcome may lead some standard statistical methods to suffer from loss of substantial power. To deal with the problem, in this study, we thus propose a rank-based test for detecting familial aggregation of a quantitative trait with the use of a within-cluster resampling process. According to our simulation studies, the proposed test expresses qualified and robust power performance. Specifically, the proposed test is slightly less powerful than the generalized estimating equations approach if the trait is normally distributed, and it is apparently more powerful if the trait distribution is essentially skewed or heavy-tailed. A user-friendly R-script and an executable file to perform the proposed test are available online to allow its implementation on ordinary research.
關鍵字 case–control family studies; familial aggregation; matched design; proband sampling; within-cluster resampling
語言 en
ISSN 0266-4763 1360-0532
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Chen, Li-ching
審稿制度
國別 GBR
公開徵稿
出版型式 紙本 電子版
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