Tom Brian Dm, Su Li, Farewell Vernon T
Medical Research Council Biostatistics Unit, Institute of Public Health, Cambridge, UK
Medical Research Council Biostatistics Unit, Institute of Public Health, Cambridge, UK.
Stat Methods Med Res. 2016 Oct;25(5):2014-2020. doi: 10.1177/0962280213509798. Epub 2013 Nov 6.
For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally.
对于由真实零值和连续分布的正值混合而成的半连续数据,使用两部分混合模型提供了一个便利的建模框架。然而,从此类模型中推导总体平均(边际)效应并非总是直截了当的。苏等人提出了一个模型,该模型为两部分模型的逻辑斯蒂部分提供了便利的边际效应估计,但该论文中提出的模型连续部分的边际效应设定基于一个错误的公式。我们提出了一个修正后的公式,并额外探讨了使用两部分模型来推断总体边际均值,这在我们的应用以及更广泛的应用中可能具有更大的实际相关性。