Randomized control trials (RCTs) have long been the gold standard for allowing causal
inferences to be made regarding the efficacy of a treatment under investigation, but
traditional RCT data analysis perspectives do not take into account a common reality:
imperfect participant compliance to treatment. Recent advances in both maximum likelihood
parameter estimation and mixture modeling methodology have enabled treatment effects to
be estimated, in the presence of less than ideal levels of participant compliance, via a …