Biostatistics Unit, St Joseph's Healthcare, 50 Charlton Ave E, Canada.
Stat Med. 2013 Mar 15;32(6):1054-72. doi: 10.1002/sim.5640. Epub 2012 Oct 10.
Longitudinal data arising from routine follow-up of patients will often have irregular measurement times. Existing methods for analysis include joint modelling of the outcome and measurement processes, and inverse-intensity weighting (IIW). This work extends previously proposed analysis of increments to the case of irregular follow-up, yielding a model for the increments that can be used as a stand-alone method. Furthermore, we propose two ways of combining the increments and IIW estimators. First, we use the increment model to select the truncation point for the inverse-intensity weights that minimises the mean squared error of the IIW estimator. Second, we use the increment model to augment the usual IIW estimating equations to form a doubly robust estimator. We evaluate the methods through simulation and apply these to a recent study of juvenile dermatomyositis.
从患者常规随访中产生的纵向数据通常具有不规则的测量时间。现有的分析方法包括对结果和测量过程进行联合建模，以及逆强度加权（Inverse-Intensity Weighting，IIW）。这项工作将以前提出的增量分析扩展到不规则随访的情况，得出了一种可作为独立方法使用的增量模型。此外，我们还提出了两种结合增量和 IIW 估计量的方法。首先，我们使用增量模型来选择逆强度权重的截断点，该截断点可使 IIW 估计量的均方误差最小化。其次，我们使用增量模型来扩充通常的 IIW 估计方程，形成双重稳健估计量。我们通过模拟来评估这些方法，并将其应用于最近的青少年皮肌炎研究。
