Robust inference for variance components models in families ascertained through probands: I. Conditioning on proband's phenotype
Robust inference for variance components models in families ascertained through probands: I. Conditioning on proband's phenotype
复制标题
通过先证者确定的家庭中方差分量模型的稳健推断：I. 先证者表型的调节
作者：
T. Beaty;K. Liang;D. Rao
本文提出了一种稳健的估计方差分量标准误的方法，该方法利用一个具有极端表型值的先证者确定的家系的数量表型。使用多元正态分布作为“工作似然”的估计量是通过在牛顿-拉夫森方法中计算条件似然、条件一阶和二阶导数来获得的。还提供了估计量的标准误差的稳健估计。假设检验基于评分检验的修改，其允许放宽多元正态性的假设。提出了条件拟合优度统计量，可用于检查单独谱系与整体模型的拟合。这种稳健的方法估计方差分量的标准误差的条件先证者的表型将允许一般的推论，从分析确定的家庭通过先证者极端或不寻常的表型，应该是最适合研究许多生理性状，可能是内在的非正常。
A robust approach for estimating standard errors of variance components by using quantitative phenotypes from families ascertained through a proband with an extreme phenotypic value is presented. Estimators that use the multivariate normal distribution as a “working likelihood” are obtained by computing conditional In‐likelihoods, conditional first and second derivatives in a Newton‐Raphson approach. Robust estimates of standard errors about the estimators are also provided. Tests of hypotheses are based on a modification of the score test, which allows the assumption of multivariate normality to be relaxed. Conditional goodness‐of‐fit statistics are proposed that can be used to examine the fit of separate pedigrees to the overall model. This robust approach for estimating the standard errors for variance components by conditioning on the proband's phenotype will allow general inferences to be made from the analysis of families ascertained through probands with extreme or unusual phenotypes and should be most appropriate for studying many physiological traits that may be intrinsically nonnormal.