2019/07/10 by Adrian Dobra, Dobra, Adrian, Katherine Buhikire +3
Mathematics · #Applications (stat.AP) #FOS: Computer and information sciences #Methodology (stat.ME) #stat.AP #stat.ME
paper · pdf · doi:10.48550/arxiv.1907.04838
17 pages, 3 figures
arxiv created 2019/07/10 · arxiv updated 2019/07/11
We empirically demonstrate that graphical models can be a valuable tool in the identification of mediating variables in causal pathways. We make use of graphical models to elucidate the causal pathway through which the treatment influences the levels of fatigue and weakness in people living with HIV (PLHIV) based on a secondary analysis of a categorical dataset collected in a behavioral clinical trial: is weakness a mediator for the treatment and fatigue, or is fatigue a mediator for the treatment and weakness? Causal mediation analysis could not offer any definite answers to these questions. KEYWORDS: Contingency tables; graphical models; loglinear models; HIV; mediation