Asar Ozgür, Ilk Ozlem
CHICAS, Lancaster Medical School, Faculty of Health and Medicine, Lancaster LA1 4YG, UK.
Department of Statistics, Faculty of Arts and Sciences, Middle East Technical University, Ankara 06800, Turkey.
Comput Methods Programs Biomed. 2014 Jul;115(3):135-46. doi: 10.1016/j.cmpb.2014.04.005. Epub 2014 Apr 19.
Most of the available multivariate statistical models dictate on fitting different parameters for the covariate effects on each multiple responses. This might be unnecessary and inefficient for some cases. In this article, we propose a modelling framework for multivariate marginal models to analyze multivariate longitudinal data which provides flexible model building strategies. We show that the model handles several response families such as binomial, count and continuous. We illustrate the model on the Kenya Morbidity data set. A simulation study is conducted to examine the parameter estimates. An R package mmm2 is proposed to fit the model.
大多数现有的多元统计模型要求针对协变量对每个多元响应的影响拟合不同的参数。在某些情况下，这可能既不必要也无效率。在本文中，我们提出了一个用于多元边际模型的建模框架，以分析多元纵向数据，该框架提供了灵活的模型构建策略。我们表明该模型可处理多个响应族，如二项式、计数和连续响应族。我们在肯尼亚发病率数据集上展示了该模型。进行了一项模拟研究以检验参数估计。我们提出了一个R包mmm2来拟合该模型。
