Lee Myungok, Lee Keunbaik, Lee Jungbok
Sekolah Pelita Harapan International Jl. Dago Permai No. 1, Komplek Dago Villas Lippo Cikarang, Bekasi, 17550, Indonesia.
Biom J. 2014 Mar;56(2):230-42. doi: 10.1002/bimj.201200085. Epub 2014 Jan 15.
In longitudinal studies investigators frequently have to assess and address potential biases introduced by missing data. New methods are proposed for modeling longitudinal categorical data with nonignorable dropout using marginalized transition models and shared random effects models. Random effects are introduced for both serial dependence of outcomes and nonignorable missingness. Fisher-scoring and Quasi-Newton algorithms are developed for parameter estimation. Methods are illustrated with a real dataset.
在纵向研究中，研究人员经常需要评估和处理由缺失数据引入的潜在偏差。本文提出了新的方法，用于使用边际化转换模型和共享随机效应模型对具有不可忽略缺失值的纵向分类数据进行建模。针对结果的序列依赖性和不可忽略的缺失性都引入了随机效应。开发了Fisher评分和拟牛顿算法用于参数估计。并用一个真实数据集对方法进行了说明。
