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Semiparametric profile likelihood estimation for continuous outcomes with excess zeros in a random-threshold damage-resistance model.

ABSTRACT: Continuous outcome data with a proportion of observations equal to zero (often referred to as semicontinuous data) arise frequently in biomedical studies. Typical approaches involve two-part models, with one part a logistic model for the probability of observing a zero and some parametric continuous distribution for modeling the positive part of the data. We propose a semiparametric model based on a biological system with competing damage manifestation and resistance processes. This allows us to derive a closed-form profile likelihood based on the retro-hazard function, leading to a flexible procedure for modeling continuous data with a point mass at zero. A simulation study is presented to examine the properties of the method in finite samples. We apply the method to a data set consisting of pulmonary capillary hemorrhage area in lab rats subjected to diagnostic ultrasound. Copyright © 2017 John Wiley & Sons, Ltd.

SUBMITTER: Rice JD

PROVIDER: S-EPMC5530377 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Semiparametric profile likelihood estimation for continuous outcomes with excess zeros in a random-threshold damage-resistance model.

Rice John D JD Tsodikov Alex A

Statistics in medicine 20170213 12

Continuous outcome data with a proportion of observations equal to zero (often referred to as semicontinuous data) arise frequently in biomedical studies. Typical approaches involve two-part models, with one part a logistic model for the probability of observing a zero and some parametric continuous distribution for modeling the positive part of the data. We propose a semiparametric model based on a biological system with competing damage manifestation and resistance processes. This allows us to ...[more]

PMID: 28192863

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