Testing the trajectory difference in a semi-parametric longitudinal model.
Testing the trajectory difference in a semi-parametric longitudinal model.
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DOI：
10.1177/0962280215584109
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发表时间：
2017-06
影响因子：
2.3
通讯作者：
Ma JZ
中科院分区：
文献类型：
--
作者：
Niu F;Zhou J;Le TH;Ma JZ
受肾脏疾病临床试验研究中肾功能进行性下降的遗传学研究的启发，我们开发了一种在半参数建模框架下评估群体轨迹差异的实用检验。对于纵向数据的时间模式或轨迹，使用B-Spline非参数逼近函数。这种近似将弹道差检验问题渐近地转化为回归系数的显着性检验问题，而回归系数的显着性检验可以用广义估计方程来简单地估计。为了选择B-Spline的最优内节点数，利用广义残差平方和准则进行了交叉验证。新提出的检验方法成功地检测到了肾脏疾病进展过程中潜在的遗传影响的显著差异，这一点没有被参数方法捕捉到。
Motivated by a genetic investigation on the progressive decline of renal function in a clinical trial study of kidney disease, we develop a practical test for evaluating the group difference in trajectories under a semi-parametric modeling framework. For the temporal patterns or trajectories of longitudinal data, B-splines are used to approximate the function non-parametrically. Such approximation asymptotically converts the problem of testing trajectory difference into the significance test of regression coefficients that can be simply estimated by generalized estimating equations. To select the optimal number of inner knots for B-splines, a cross-validation procedure is performed using the criterion of generalized residual sum of squares. The new proposed test successfully detects the significant difference of underlying genetic impact on the progression of renal disease, which is not captured by the parametric approach.