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Abstract:
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Zero-inflated continuous (or semi-continuous) data arise frequently in medical, economical, and ecological studies. Examples include substance abuse, medical costs, medical care usage, coronary artery calcium score, and daily precipitation levels. Such data are often characterized by the presence of a large portion of zero values in addition to continuous non-zero (i.e., positive) values that are often skewed to the right and heteroscedastic. Both features suggest no simple parametric distribution is suitable for describing such "zero-inflated continuous" data. In this short course, we will review statistical methods to analyze zero-inflated continuous data. We will start from the cross-sectional zero-inflated continuous data. The second section involves modeling repeated measures zero-inflated continuous data. Finally, we will present applications to real data sets to illustrate our methods. We will use alcohol drinking data and correlated medical costs as examples. SAS codes will be provided to facilitate the applications of these methods. Model comparison also will be conducted and we will present the related topics in survival analysis.
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