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Zero‐inflated count outcomes arise quite often in research and practice. Parametric models such as the zero‐inflated Poisson and zero‐inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution‐free, or semi‐parametric, alternatives...
Estimating causal treatment effect for randomized controlled trials under post‐treatment confounding, that is, noncompliance and informative dropouts, is becoming an important problem in intervention/prevention studies when the treatment exposures are not completely controlled. When confounding is present in a study, the traditional intention‐to‐treat approach could underestimate the treatment effect...
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