  The three state illness death model has been established as a general
approach for regression analysis of semi competing risks data. For
observational data the marginal structural models (MSM) are a useful tool,
under the potential outcomes framework to define and estimate parameters with
causal interpretations. In this paper we introduce a class of marginal
structural illness death models for the analysis of observational semi
competing risks data. We consider two specific such models, the Markov illness
death MSM and the frailty based Markov illness death MSM. For interpretation
purposes, risk contrasts under the MSMs are defined. Inference under the
illness death MSM can be carried out using estimating equations with inverse
probability weighting, while inference under the frailty based illness death
MSM requires a weighted EM algorithm. We study the inference procedures under
both MSMs using extensive simulations, and apply them to the analysis of mid
life alcohol exposure on late life cognitive impairment as well as mortality
using the Honolulu Asia Aging Study data set. The R codes developed in this
work have been implemented in the R package semicmprskcoxmsm that is publicly
available on CRAN.
