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.

Faculty of Mathematics and Physics Charles University Prague Czech Republic

Leuven Biostatistics and Statistical Bioinformatics Centre University of Leuven Leuven Belgium

Leuven Institute for Healthcare Policy University of Leuven Leuven Belgium

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Identifying influential observations in a Bayesian multi-level mediation model