Cordell H J, Olson J M
Department of Epidemiology and Biostatistics, Rammelkamp Center for Education and Research, MetroHealth Campus, Case Western Reserve University, Cleveland, Ohio 44109, USA.
Genet Epidemiol. 2000 Apr;18(4):307-21. doi: 10.1002/(SICI)1098-2272(200004)18:4<307::AID-GEPI4>3.0.CO;2-3.
Locus-specific sibling relative risk is often estimated using affected-sib-pair lod score analysis of affected sibships and may be used to decide whether to continue or discontinue the search for additional susceptibility genes. We showed that relative-risk estimates obtained using affected-sib-pair data are asymptotically unbiased when each pair is given a weight inversely proportional to the sibship ascertainment probability. Here we show by simulation that the extent of the bias of relative risks estimated using the incorrect ascertainment weights is small for dominant models, but large for single-locus recessive models and some two-locus heterogeneity models. Since in practice the ascertainment scheme is often unknown, we investigate methods for jointly estimating ascertainment and relative risks from affected-sibship data. Given a sufficient sample size, a reasonable estimate of relative risk may always be obtained using only affected pairs from sibships with two affected and no unaffected siblings. This estimate, which has a large variance, may then be used in a three-stage procedure (which we call the alpha method) to estimate consistently both the ascertainment probabilities and the relative risks with greater precision. We additionally propose correction factors to eliminate small-sample bias of relative risks and investigate the bias due to error in the estimate of disease locus location.
特定基因座的同胞相对风险通常通过对患病同胞对的患病同胞组进行患病同胞对对数优势计分分析来估计,并且可用于决定是否继续或停止寻找其他易感基因。我们表明,当给每一对赋予与同胞组确诊概率成反比的权重时,使用患病同胞对数据获得的相对风险估计值是渐近无偏的。在此我们通过模拟表明,对于显性模型,使用错误的确诊权重估计的相对风险偏差程度较小,但对于单基因座隐性模型和一些双基因座异质性模型则偏差较大。由于在实际中确诊方案通常是未知的,我们研究了从患病同胞组数据联合估计确诊概率和相对风险的方法。给定足够大的样本量,仅使用有两个患病且无未患病同胞的同胞组中的患病对,总能获得相对风险的合理估计值。这个估计值方差较大,然后可用于一个三阶段程序(我们称之为α方法),以更精确地一致估计确诊概率和相对风险。我们还提出了校正因子以消除相对风险的小样本偏差,并研究由于疾病基因座位置估计误差导致的偏差。