A B-Spline Based Semiparametric Nonlinear Mixed Effects Model

A B-Spline Based Semiparametric Nonlinear Mixed Effects Model
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DOI:
10.1198/jcgs.2010.09001
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发表时间:
2011-01
影响因子:
2.4
通讯作者:
A. Elmi;S. Ratcliffe;S. Parry;Wensheng Guo
A. Elmi;S. Ratcliffe;S. Parry;Wensheng Guo
中科院分区:
数学2区
文献类型:
--
作者:
A. Elmi;S. Ratcliffe;S. Parry;Wensheng Guo

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半参数非线性混合效应模型(SNMM)(Ke和Wang 2001)为组间曲线形状的纵向比较提供了灵活的框架。在这篇文章中,我们开发了一种替代方法来拟合SNMM重新制定柯和王的平滑样条为基础的模型的B样条。现有的算法是基于一个backfitting过程,迭代两个混合模型,其相应的似然不等于所有模型参数的可能性。其结果是缺乏可靠的收敛性和统计推断。然而,使用B样条,克服了这些缺点,简化了似然计算,而不牺牲模型的灵活性。因此,该算法可以用基于自适应高斯求积的现有准确技术来表达。该模型适用于分娩曲线,子宫颈扩张纵向测量,从妇女试图剖宫产后阴道分娩。在子宫破裂需要紧急剖腹产的情况下,仅测量了部分曲线,而对照组自然分娩。该模型使我们能够估计和比较病例和对照组之间的平均产程曲线形状,并确定临床医生可以区分不同组平均产程曲线的最早时间。补充材料可在线获取。
The Semiparametric Nonlinear Mixed Effects Model (SNMM) (Ke and Wang 2001) provides a flexible framework for longitudinal comparisons of curve shapes between groups. In this article, we develop an alternative method for fitting the SNMM by reformulating Ke and Wang’s smoothing spline based model in terms of B-splines. The existing algorithm is based on a backfitting procedure that iterates between two mixed models whose corresponding likelihoods are not equivalent to the likelihood of all model parameters. The consequence is a lack of reliable convergence and statistical inference. Using B-splines, however, overcomes these disadvantages by simplifying the likelihood computations without sacrificing model flexibility. Therefore, the algorithm can be expressed in terms of existing, accurate techniques based on Adaptive Gaussian Quadrature. The model is applied to labor curves, cervical dilation measured longitudinally, from women attempting a vaginal birth after cesarean. Only partial curves were measured on cases of uterine rupture given the need for emergency c-section while controls completed delivery naturally. The model allowed us to estimate and compare the average labor curve shape between cases and controls and also determine the earliest time at which clinicians could distinguish between the average labor curves in different groups. Supplemental materials are available online.