On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice.
On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice.
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DOI：
10.1002/sim.7643
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发表时间：
2018-07-10
影响因子：
2
通讯作者：
White IR
中科院分区：
文献类型：
--
作者：
Tompsett DM;Leacy F;Moreno-Betancur M;Heron J;White IR
非随机完全条件规范（NARFCS）程序为非随机缺失条件下的多变量缺失数据插补提供了一种灵活的方法。最近的工作已经概述了从专家意见中引出程序的敏感性参数的困难，因为它们的条件性。未能充分说明这种调节作用将产生与用户假设不一致的插补。在本文中，我们澄清的重要性，正确的调节NARFCS的灵敏度参数和开发程序来校准这些灵敏度参数，将它们与更容易引起的数量，特别是，从简单的模式混合模型的灵敏度参数。此外，我们考虑如何将缺失指标作为NARFCS估算模型的一部分，建议将所有这些指标作为默认做法纳入每个模型。算法的开发，以执行校准程序，并证明从雅芳纵向研究的父母和孩子的数据，以及模拟研究。
The not‐at‐random fully conditional specification (NARFCS) procedure provides a flexible means for the imputation of multivariable missing data under missing‐not‐at‐random conditions. Recent work has outlined difficulties with eliciting the sensitivity parameters of the procedure from expert opinion due to their conditional nature. Failure to adequately account for this conditioning will generate imputations that are inconsistent with the assumptions of the user. In this paper, we clarify the importance of correct conditioning of NARFCS sensitivity parameters and develop procedures to calibrate these sensitivity parameters by relating them to more easily elicited quantities, in particular, the sensitivity parameters from simpler pattern mixture models. Additionally, we consider how to include the missingness indicators as part of the imputation models of NARFCS, recommending including all of them in each model as default practice. Algorithms are developed to perform the calibration procedure and demonstrated on data from the Avon Longitudinal Study of Parents and Children, as well as with simulation studies.
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DOI：
10.1111/j.2517-6161.1977.tb01600.x
发表时间：
1977-01-01
期刊：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL
影响因子：
--
作者：
DEMPSTER, AP;LAIRD, NM;RUBIN, DB
通讯作者：
RUBIN, DB
影响因子：
7.7
作者：
Cornish RP;Tilling K;Boyd A;Davies A;Macleod J
通讯作者：
Macleod J
影响因子：
2.3
作者：
Moreno-Betancur, M.;Chavance, M.
通讯作者：
Chavance, M.
影响因子：
3.7
作者：
Wallace P;Murray E;McCambridge J;Khadjesari Z;White IR;Thompson SG;Kalaitzaki E;Godfrey C;Linke S
通讯作者：
Linke S
影响因子：
2
作者：
White, Ian R.;Royston, Patrick;Wood, Angela M.
通讯作者：
Wood, Angela M.