Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic.
Leuven Biostatistics and Statistical Bioinformatics Centre, University of Leuven, Leuven, Belgium.
Stat Med. 2018 May 10;37(10):1650-1670. doi: 10.1002/sim.7605. Epub 2018 Feb 20.
Although increasingly complex models have been proposed in mediation literature, there is no model nor software that incorporates the multiple possible generalizations of the simple mediation model jointly. We propose a flexible moderated mediation model allowing for (1) a hierarchical structure of clustered data, (2) more and possibly correlated mediators, and (3) an ordinal outcome. The motivating data set is obtained from a European study in nursing research. Patients' willingness to recommend their treating hospital was recorded in an ordinal way. The research question is whether such recommendation directly depends on system-level features in the organization of nursing care, or whether these associations are mediated by 2 measurements of nursing care left undone and possibly moderated by nurse education. We have developed a Bayesian approach and accompanying program that takes all the above generalizations into account.
尽管中介文献中提出了越来越复杂的模型，但没有一个模型或软件能够联合纳入简单中介模型的多种可能推广。我们提出了一个灵活的中介调节模型，允许（1）聚类数据的层次结构，（2）更多且可能相关的中介，以及（3）有序结果。激励性数据集来自护理研究的一项欧洲研究。患者对推荐其治疗医院的意愿以有序的方式记录。研究问题是，这种推荐是否直接取决于护理组织中系统层面的特征，或者这些关联是否通过 2 项未完成的护理测量来中介，并且可能由护士教育来调节。我们已经开发了一种贝叶斯方法和相应的程序，该方法考虑了所有上述推广。
