Premium
Multilevel moderated mediation model with ordinal outcome
Author(s) -
Rusá Šárka,
Komárek Arnošt,
Lesaffre Emmanuel,
Bruyneel Luk
Publication year - 2018
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.7605
Subject(s) - mediation , moderated mediation , outcome (game theory) , bayesian probability , set (abstract data type) , multilevel model , hierarchical database model , ordinal regression , computer science , psychology , econometrics , social psychology , data mining , artificial intelligence , mathematics , machine learning , mathematical economics , programming language , political science , law
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.