Statistical methods for pediatric research

我的研究集中在三个领域：荟萃分析的统计方法、因果推断和妊娠结局的方法。与Khajak Ishak(2006年博士毕业)一起，我在多变量数据的荟萃分析方面做了大量工作。我们证明，多变量数据的荟萃分析并不总是提供益处，特别是当多变量结果之间的相关性来自于治疗效果之间的相关性以外的来源时(例如研究的异质性)。我将继续致力于基于多项分布的贝叶斯方法和个人患者数据(而不是汇总数据)的多变量结果的新模型。我将使用频率分析和贝叶斯分析技术来实现我们的模型，无论是在模拟中还是在真实数据中。正如我和其他人所指出的那样，怀孕结果带来了许多统计挑战。特别是，我对胎龄的作用感兴趣。胎龄是一个重要的围产儿预测指标，但容易受到系统性和随机性错误分类的影响。我将把我关于胎龄测量误差的工作扩展到多变量数据；当有关出生长度、头围和其他特征的信息可用时，它们应该提供关于胎龄误差可能性的补充信息。此外，我将为这个测量误差开发一个更一般的模型，我最初的模型是其中的一个特例。典型的孕周分析将测量误差和随后的分析视为独立的问题。生存分析的贝叶斯方法。最后，我打算将基于潜在结果的因果推理理论(Rubin 1976，Robins 1987和随后的论文)应用到几个环境中。我将开发和比较逆概率加权估计程序的模型选择方法，并开发基于主分层的不符合条件的随机试验方法。

My research centres on three areas: statistical methods for meta-analysis, causal inference, and methods for pregnancy outcomes. With Khajak Ishak (PhD graduate 2006) I have done extensive work on meta-analysis of multivariate data. We demonstrated that meta-analysis of multivariate data does not always provide benefit, in particular when correlation between the multivariate outcomes comes from sources other than correlation among treatment effects (eg study heterogeneity). I will continue to work on a new model for multivariate outcomes based on a Bayesian approach to a multinomial distribution, and individual patient data (rather than summary data). Iwill implement our model using frequentist and Bayesian analytic techniques, both in simulation and in real data. As I and others have noted, pregnancy outcomes pose many statistical challenges. In particular, I am interested in the role of gestational age. Gestational age is an important perinatal predictor, but is subject to both systematic and random misclassification. I will extend my work on measurement error in gestational age to multivariate data; when information on birth length, head circumference and other characteristics are available, they should provide added information on the likelihood of errors in gestational age. In addition, I will develop a more general model for this measurement error, of which my original model represents a special case. Typical analyses of gestational age have treated the measurement error and subsequent analyses as separate problems. Bayesian approaches to survival analysis. Finally, I intend to apply the theory of causal inference based on potential outcomes (Rubin 1976, Robins 1987 and subsequent papers) in several settings. I will develop and compare methods for model selection for inverse probability weighted estimation procedures, and develop principal-stratification based methods for randomized trials with noncompliance.