Inferential challenges that arise when data are censored have been extensively studied under the classical frameworks. In this paper, we provide an alternative generalized inferential model approach whose output is a data-dependent plausibility function. This construction driven by association between distribution of relative likelihood function at interest parameter and unobserved auxiliary va...